Data mining recently made big news with the Cambridge Analytica scandal, but it is not just for ads and politics. It can help doctors spot fatal infections and it can even predict massacres in the Congo. Hosted by: Stefan Chin Head to https://scishowfinds.com/ for hand selected artifacts of the universe! ---------- Support SciShow by becoming a patron on Patreon: https://www.patreon.com/scishow ---------- Dooblydoo thanks go to the following Patreon supporters: Lazarus G, Sam Lutfi, Nicholas Smith, D.A. Noe, سلطان الخليفي, Piya Shedden, KatieMarie Magnone, Scott Satovsky Jr, Charles Southerland, Patrick D. Ashmore, Tim Curwick, charles george, Kevin Bealer, Chris Peters ---------- Looking for SciShow elsewhere on the internet? Facebook: http://www.facebook.com/scishow Twitter: http://www.twitter.com/scishow Tumblr: http://scishow.tumblr.com Instagram: http://instagram.com/thescishow ---------- Sources: https://www.aaai.org/ojs/index.php/aimagazine/article/viewArticle/1230 https://www.theregister.co.uk/2006/08/15/beer_diapers/ https://www.theatlantic.com/technology/archive/2012/04/everything-you-wanted-to-know-about-data-mining-but-were-afraid-to-ask/255388/ https://www.economist.com/node/15557465 https://blogs.scientificamerican.com/guest-blog/9-bizarre-and-surprising-insights-from-data-science/ https://qz.com/584287/data-scientists-keep-forgetting-the-one-rule-every-researcher-should-know-by-heart/ https://www.amazon.com/Predictive-Analytics-Power-Predict-Click/dp/1118356853 http://dml.cs.byu.edu/~cgc/docs/mldm_tools/Reading/DMSuccessStories.html http://content.time.com/time/magazine/article/0,9171,2058205,00.html https://www.nytimes.com/2012/02/19/magazine/shopping-habits.html?pagewanted=all&_r=0 https://www2.deloitte.com/content/dam/Deloitte/de/Documents/deloitte-analytics/Deloitte_Predictive-Maintenance_PositionPaper.pdf https://www.cs.helsinki.fi/u/htoivone/pubs/advances.pdf http://cecs.louisville.edu/datamining/PDF/0471228524.pdf https://bits.blogs.nytimes.com/2012/03/28/bizarre-insights-from-big-data https://scholar.harvard.edu/files/todd_rogers/files/political_campaigns_and_big_data_0.pdf https://insights.spotify.com/us/2015/09/30/50-strangest-genre-names/ https://www.theguardian.com/news/2005/jan/12/food.foodanddrink1 https://adexchanger.com/data-exchanges/real-world-data-science-how-ebay-and-placed-put-theory-into-practice/ https://www.theverge.com/2015/9/30/9416579/spotify-discover-weekly-online-music-curation-interview http://blog.galvanize.com/spotify-discover-weekly-data-science/ Audio Source: https://freesound.org/people/makosan/sounds/135191/ Image Source: https://commons.wikimedia.org/wiki/File:Swiss_average.png
Views: 151887 SciShow
This short revision video introduces the concept of data mining. Data mining is the process of analysing data from different perspectives and summarising it into useful information, including discovery of previously unknown interesting patterns, unusual records or dependencies. There are many potential business benefits from effective data mining, including: Identifying previously unseen relationships between business data sets Better predicting future trends & behaviours Extract commercial (e.g. performance insights) from big data sets Generating actionable strategies built on data insights (e.g. positioning and targeting for market segments) Data mining is a particularly powerful series of techniques to support marketing competitiveness. Examples include: Sales forecasting: analysing when customers bought to predict when they will buy again Database marketing: examining customer purchasing patterns and looking at the demographics and psychographics of customers to build predictive profiles Market segmentation: a classic use of data mining, using data to break down a market into meaningful segments like age, income, occupation or gender E-commerce basket analysis: using mined data to predict future customer behavior by past performance, including purchases and preferences
Views: 5722 tutor2u
In this video we describe data mining, in the context of knowledge discovery in databases. More videos on classification algorithms can be found at https://www.youtube.com/playlist?list=PLXMKI02h3_qjYoX-f8uKrcGqYmaqdAtq5 Please subscribe to my channel, and share this video with your peers!
Views: 238440 Thales Sehn Körting
Why do so many companies make bad decisions, even with access to unprecedented amounts of data? With stories from Nokia to Netflix to the oracles of ancient Greece, Tricia Wang demystifies big data and identifies its pitfalls, suggesting that we focus instead on "thick data" -- precious, unquantifiable insights from actual people -- to make the right business decisions and thrive in the unknown. Check out more TED talks: http://www.ted.com The TED Talks channel features the best talks and performances from the TED Conference, where the world's leading thinkers and doers give the talk of their lives in 18 minutes (or less). Look for talks on Technology, Entertainment and Design -- plus science, business, global issues, the arts and more. Follow TED on Twitter: http://www.twitter.com/TEDTalks Like TED on Facebook: https://www.facebook.com/TED Subscribe to our channel: https://www.youtube.com/TED
Views: 106158 TED
In this Data Mining Fundamentals tutorial, we continue our introduction to similarity and dissimilarity by discussing euclidean distance and cosine similarity. We will show you how to calculate the euclidean distance and construct a distance matrix. -- Learn more about Data Science Dojo here: https://hubs.ly/H0hCsHC0 Watch the latest video tutorials here: https://hubs.ly/H0hCsnR0 See what our past attendees are saying here: https://hubs.ly/H0hCsnT0 -- At Data Science Dojo, we believe data science is for everyone. Our in-person data science training has been attended by more than 4000+ employees from over 830 companies globally, including many leaders in tech like Microsoft, Apple, and Facebook. -- Like Us: https://www.facebook.com/datasciencedojo Follow Us: https://plus.google.com/+Datasciencedojo Connect with Us: https://www.linkedin.com/company/datasciencedojo Also find us on: Google +: https://plus.google.com/+Datasciencedojo Instagram: https://www.instagram.com/data_science_dojo Vimeo: https://vimeo.com/datasciencedojo
Views: 26813 Data Science Dojo
The Rest Of Us on Patreon: https://www.patreon.com/TheRestOfUs The Rest Of Us on Twitter: http://twitter.com/TROUchannel The Rest Of Us T-Shirts and More: http://teespring.com/TheRestOfUsClothing Credits: Jaron Lanier: Who Owns the Future Georg Polzer: Designing the Data Economy https://www.youtube.com/watch?v=OILe_ikGTSc
Views: 210009 The Rest Of Us
How companies are making money out of Big Data? Big Data is mainly mining and processing of large chunk of data which ultimately helps in the growth of the company. With Big Data companies are now able to judge or predict the customer behavior or interest which helps in shaping up brand values. Companies are getting more involved into Big Data and making money out it. Companies are trying to make Big Data available in one place to allowing hundreds of people to use it. Consumer behavior data is analyzed to generate greater revenue. Social media is contributing greatly in commercializing Big Data and companies are spending large amount of money to understand the customer behavior using media with help of targeted advertising. Consumer focused business are generating more revenue and Big Data helps greatly in study of the behavior. Let us see at two great examples where companies are making great money out of it – Companies mainly the social networking companies are generating large sales studying the customer behavior. Badoo is one such company which is the largest growing social networking company for meeting new guys. Gaming companies are also building projects around Big Data by analyzing people interests in games and they are presenting targeted advertisements for the companies to advertise to consumers for product development. IsCool Entertainment is one such company which is analyzing customer online gaming interest and working on it. Big Data interests are growing rapidly in the industry and more companies are looking to hire Big Data specialists to contribute in the revenue generation. Shifting to new technology is must and Big Data is the one that is making the difference. http://www.bigdataversity.org/
Views: 63 Support Team
This video discuss How to become a data analyst in India. For more videos on Jobs &Careers :https://www.youtube.com/channel/UCEFTTJFLp4GipA7BLZNTXvA?view_as=subscriber For aptitude classes :https://www.youtube.com/watch?v=lxm6ez2cx6Y&list=PLjLhUHPsqNYnM1DmZhIbtd9wNhPO1HGPT Every business collects data such as sales figures, market research, logistics, or transportation costs. A data analyst's job is to take that data and analyse it to help companies make better business decisions. Some examples of a data analyst basic job functions include: 1) estimating market shares; 2) establishing a price of new materials for the market; 3) reducing transportation costs; 4) timing of sales and 5) figuring out when to hire or reduce the workforce.Data analysts are responsible for collecting, manipulating, and analyzing data. How To Get There? By obtaining a university degree, learning important analytical skills, and gaining valuable work experience, you can become a successful data analyst. A bachelor's degree is needed for most entry-level jobs, and a master's degree will be needed for many upper-level jobs. To become an initial level data analyst, you’ll have to earn a degree in a subject such as mathematics, statistics, economics, marketing, finance, or computer science. Higher level data analyst jobs may require a master’s or doctoral degree, and they usually guarantee higher pay. Individuals looking for data analyst jobs must be knowledgeable in computer programs such as Microsoft Excel, Microsoft Access, SharePoint, and SQL databases. Data analysts also must have good communication skills, as they must have an open line of communication with the companies with which they work. Lets see some of the Best courses on Analytics offered in India. 1. Advanced Analytics for Management – IIM This program enables practitioners, managers, and decision-makers to use advanced analytics for better decision-making 2. Analytics Essentials – IIIT, Bangalore “Analytics Essentials”is a 3 months week-end program by International Institute of Information Technology Bangalore (IIITB)providing a foundational certification course in Business Analytics 3. Business Analytics and Intelligence (BAI) – IIM Bangalore This course provides in-depth knowledge of handling data and Business Analytics’ tools that can be used for fact-based decision-making. The participants will be able to analyse and solve problems from different industries such as manufacturing, service, retail, software, banking and finance, sports, pharmaceutical, aerospace etc. 4. Certificate Program in Business Analytics – ISB, Hyderabad A combination of classroom and Technology aided learning platform, .Participants will typically be on campus for a 5 day schedule of classroom learning every alternate month for a span of 12 months, which would ideally be planned to include a weekend. 5. Data Analysis Online courses – SRM University SRM University offers part time online courses in data analysis in collaboration with Coursera, edX, Udacity. 6. Executive Program in Business Analytics – IIM Calcutta This executive 1 year long distance program is designed to expose participants to the tools and techniques of analytics. The program covers topics such as Data Mining, Soft Computing, Design of Experiments, Survey Sampling, Statistical Inference, Investment Management, Financial Modelling, Advanced marketing Research etc. 7. Executive Program in Business Analytics and Business Intelligence – IIM Ranchi Course duration is 3 months. Classes will be conducted by eminent professors and industry experts in the weekends in Mumbai/ Kolkata /Delhi /Bengaluru and in addition to these, there will be one-week learning in IIM Ranchi. 8. Jigsaw Academy courses Jigsaw Academy provides some online analytics courses.Their courses include; Foundation Course in Analytics Data Science Certification Human Resources (HR) Analytics Course Big Data Analytics Using Hadoop and R Advanced Certification in Retail Analytics Advanced Course in Financial Analytics Analytics with R Great Lakes PG Course in Business Analytics 9. M. Tech. Computer Science and Engineering with Specialization in Big Data Analytics – VIT VIT offers full time course in Big Data analysis to promote an academic career for further research in theoretical as well as applied aspects of Big Data Analytics 10. M.Tech (Database Systems) – SRM University SRM University offers a two year full time course in database systems where the students are exposed to theoretical concepts complemented by related practical experiments. 11. M.Tech Computer Engineering and Predictive Analytics – Crescent Engineering College Salary The Salary of Data analysts depends on job responsibilities. An entry-level data analyst with basic technical tools might be looking at anything from Rs. 5 lakhs to 12 lakhs per year. A senior data analyst with the skills of a data scientist can command a high price. #dataanalyst #careeroptions #datascience
Views: 47978 Freshersworld.com Jobs & Careers
This Data Science tutorial video will give you an idea on the life of a Data Scientist, steps involved in Data science project, roles & salary offered to a Data Scientist. Data is everywhere. In fact, the amount of digital data that exists is growing at a rapid rate, doubling every two years, and changing the way we live. Data Science is basically dealing with unstructured and structured data. Data Science is a field that comprises of everything that is related to data cleansing, preparation, and analysis. In simple terms, it is the umbrella of techniques used when trying to extract insights and information from data. Now, let us get started and understand what is Data Science all about. Below topics are explained in this Data Science tutorial: 1. Life of a Data Scientist 2. Steps in Data Science project - Understanding the business problem - Data acquisition - Data preparation - Exploratory data analysis - Data modeling - Visualization and communication - Deploy & maintenance 3. Roles offered to a Data Scientist 4. Salary of a Data Scientist To learn more about Data Science, subscribe to our YouTube channel: https://www.youtube.com/user/Simplilearn?sub_confirmation=1 Read the full article here: https://www.simplilearn.com/career-in-data-science-ultimate-guide-article?utm_campaign=What-is-Data-Science-bTTxei-S1WI&utm_medium=Tutorials&utm_source=youtube Watch more videos on Data Science: https://www.youtube.com/watch?v=0gf5iLTbiQM&list=PLEiEAq2VkUUIEQ7ENKU5Gv0HpRDtOphC6 #DataScienceWithPython #DataScienceWithR #DataScienceCourse #DataScience #DataScientist #BusinessAnalytics #MachineLearning This Data Science with Python course will establish your mastery of data science and analytics techniques using Python. With this Python for Data Science Course, you’ll learn the essential concepts of Python programming and become an expert in data analytics, machine learning, data visualization, web scraping and natural language processing. Python is a required skill for many data science positions, so jumpstart your career with this interactive, hands-on course. Why learn Data Science? Data Scientists are being deployed in all kinds of industries, creating a huge demand for skilled professionals. Data scientist is the pinnacle rank in an analytics organization. Glassdoor has ranked data scientist first in the 25 Best Jobs for 2016, and good data scientists are scarce and in great demand. As a data you will be required to understand the business problem, design the analysis, collect and format the required data, apply algorithms or techniques using the correct tools, and finally make recommendations backed by data. You can gain in-depth knowledge of Data Science by taking our Data Science with python certification training course. With Simplilearn’s Data Science certification training course, you will prepare for a career as a Data Scientist as you master all the concepts and techniques. Those who complete the course will be able to: 1. Gain an in-depth understanding of data science processes, data wrangling, data exploration, data visualization, hypothesis building, and testing. You will also learn the basics of statistics. Install the required Python environment and other auxiliary tools and libraries 2. Understand the essential concepts of Python programming such as data types, tuples, lists, dicts, basic operators and functions 3. Perform high-level mathematical computing using the NumPy package and its large library of mathematical functions Perform scientific and technical computing using the SciPy package and its sub-packages such as Integrate, Optimize, Statistics, IO and Weave 4. Perform data analysis and manipulation using data structures and tools provided in the Pandas package 5. Gain expertise in machine learning using the Scikit-Learn package The Data Science with python is recommended for: 1. Analytics professionals who want to work with Python 2. Software professionals looking to get into the field of analytics 3. IT professionals interested in pursuing a career in analytics 4. Graduates looking to build a career in analytics and data science 5. Experienced professionals who would like to harness data science in their fields Learn more at: https://www.simplilearn.com/big-data-and-analytics/python-for-data-science-training?utm_campaign=What-is-Data-Science-X3paOmcrTjQ&utm_medium=Tutorials&utm_source=youtube For more information about Simplilearn’s courses, visit: - Facebook: https://www.facebook.com/Simplilearn - Twitter: https://twitter.com/simplilearn - LinkedIn: https://www.linkedin.com/company/simp... - Website: https://www.simplilearn.com Get the Android app: http://bit.ly/1WlVo4u Get the iOS app: http://apple.co/1HIO5J0
Views: 306775 Simplilearn
"The National Security Agency and the FBI are tapping directly into the central servers of nine leading U.S. Internet companies, extracting audio and video chats, photographs, e-mails, documents, and connection logs that enable analysts to track foreign targets, according to a top-secret document obtained by The Washington Post."* We now know that the NSA was and is getting phone records from millions of Americans, but the Washington Post has uncovered that the Obama administration is also overseeing data mining of 9 major internet companies under PRISM. A huge amount of personal data is being monitored more closely than most ever thought possible. Is this Obama's "change?" Cenk Uygur breaks it down. *Read more from The Washington Post: http://www.washingtonpost.com/investigations/us-intelligence-mining-data-from-nine-us-internet-companies-in-broad-secret-program/2013/06/06/3a0c0da8-cebf-11e2-8845-d970ccb04497_story.html Support The Young Turks by Subscribing http://www.youtube.com/user/theyoungturks Like Us on Facebook: Follow Us on Twitter: http://www.twitter.com/theyoungturks Support TYT for FREE by doing your Amazon shopping through this link (bookmark it!) http://www.amazon.com/?tag=theyoungturks-20 Buy TYT Merch: http://theyoungturks.spreadshirt.com/ Support The Young Turks by becoming a member of TYT Nation at http://www.tytnetwork.com/member-options/. Your membership supports the day to day operations and is vital for our continued success and growth. In exchange, we provided members only bonuses! We tape a special Post Game show Mon-Thurs and you get access to the entire live show at your convenience in video, audio and podcast formats.
Views: 34868 The Young Turks
An extensive new Oxford University study shows that governments, political parties, and NGOs spend well over half a billion dollars around the world to influence elections and public opinion, most of it in a completely unregulated and secretive manner. We speak to the study's co-author, Samantha Bradshaw Visit https://therealnews.com for more stories and help support our work by donating at https://therealnews.com/donate.
Views: 3904 The Real News Network
AI for Marketing & Growth #1 - Predictive Analytics in Marketing Download our list of the world's best AI Newsletters 👉https://hubs.ly/H0dL7N60 Welcome to our brand new AI for Marketing & Growth series in which we’ll get you up to speed on Predictive Analytics in Marketing! This series you-must-watch-this-every-two-weeks sort of series or you’re gonna get left behind.. Predictive analytics in marketing is a form of data mining that uses machine learning and statistical modeling to predict the future. Based on historical data. Applications in action are all around us already. For example, If your bank notifies you of suspicious activity on your bank card, it is likely that a statistical model was used to predict your future behavior based on your past transactions. Serious deviations from this pattern are flagged as suspicious. And that’s when you get the notification. So why should marketers care? Marketers can use it to help optimise conversions for their funnels by forecasting the best way to move leads down the different stages, turning them into qualified prospects and eventually converting them into paying customers. Now, if you can predict your customers’ behavior along the funnel, you can also think of messages to best influence that behavior and reach your customer’s highest potential value. This is super-intelligence for marketers! Imagine if you could not only determine whether a lead is a good fit for your product but also which are most promising. This’ll allow you to focus your team’s efforts on leads with the highest ROI. Which will also imply a shift in mindset. Going from quantity metrics, or how many leads you can attract, to quality metrics, or how many good leads you can engage. You can now easily predict your OMTM or KPIs in real-time and finally push vanity metrics aside. For example, based on my location, age, past purchases, and gender, how likely are you to buy eggs I if you just added milk to your basket? A supermarket can use this information to automatically recommend products to you A financial services provider can use thousands of data points created by your online behaviour to decide which credit card to offer you, and when. A fashion retailer can use your data to decide which shoes to recommend as your next purchase, based on the jacket you just bought. Sure, businesses can improve their conversion rates, but the implications are much bigger than that. Predictive analytics allows companies to set pricing strategies based on consumer expectations and competitor benchmarks. Retailers can predict demand, and therefore make sure they have the right level of stock for each of their products. The evidence of this revolution is already around us. Every time we type a search query into Google, Facebook or Amazon we’re feeding data into the machine. The machine thrives on data, growing ever more intelligent. To leverage the potential of artificial intelligence and predictive analytics, there are four elements that organizations need to put into place. 1. The right questions 2. The right data 3. The right technology 4. The right people Ok.. let’s look at some use cases of businesses that are already leveraging predictive analytics. Other topics discussed: Ai analytics case study artificial intelligence big data deep learning demand forecasting forecasting sales machine learning predictive analytics in marketing data mining statistical modelling predict the future historical data AI Marketing machine learning marketing machine learning in marketing artificial intelligence in marketing artificial intelligence AI Machine learning ------------------------------------------------------- Amsterdam bound? Want to make AI your secret weapon? Join our A.I. for Marketing and growth Course! A 2-day course in Amsterdam. No previous skills or coding required! https://hubs.ly/H0dkN4W0 OR Check out our 2-day intensive, no-bullshit, skills and knowledge Growth Hacking Crash Course: https://hubs.ly/H0dkN4W0 OR our 6-Week Growth Hacking Evening Course: https://hubs.ly/H0dkN4W0 OR Our In-House Training Programs: https://hubs.ly/H0dkN4W0 OR The world’s only Growth & A.I. Traineeship https://hubs.ly/H0dkN4W0 Make sure to check out our website to learn more about us and for more goodies: https://hubs.ly/H0dkN4W0 London Bound? Join our 2-day intensive, no-bullshit, skills and knowledge Growth Marketing Course: https://hubs.ly/H0dkN4W0 ALSO! Connect with Growth Tribe on social media and stay tuned for nuggets of wisdom, updates and more: Facebook: https://www.facebook.com/GrowthTribeIO/ LinkedIn: https://www.linkedin.com/company/growth-tribe Twitter: https://twitter.com/GrowthTribe/ Instagram: https://www.instagram.com/growthtribe/ Snapchat: growthtribe Video URL: https://youtu.be/uk82DHcU7z8
Views: 21025 Growth Tribe
This video goes over my 7 day 1 week Bitcoin Mining experiment. I let my computer Mine for Bitcoin for a week straight, to see how much money I could generate. I left my PC on while I slept and well, you'll have to watch the video to see what I made in profit. :) Links: Bitcoin Wallet: http://bitcoin.org/en/choose-your-wallet GUI Miner: https://bitcointalk.org/?topic=3878.0 BitCoin Calculator: https://bitclockers.com/calc Monitor How Many Watts Your Computer Uses:http://www.newegg.com/Product/Product.aspx?Item=N82E16882715001 MH/s Hardware Comparison: https://en.bitcoin.it/wiki/Comparison_of_mining_pools Thanks for watching, and let me know what I should do next. Thanks!
Views: 2021613 MrJayBusch
Decision Tree Tutorial and Introduction by Jigsaw Academy. This is part one of the Decision Tree tutorial from our Foundation Analytics course (http://www.jigsawacademy.com/online-analytics-training). In this example, we look at how decision trees can be used by credit card companies to market themselves to a target audience of potentially profitable customers. Jigsaw Academy is an award winning premier online analytics training institute that aims to meet the growing demand for talent in the field of analytics by providing industry-relevant training to develop business-ready professionals.Jigsaw Academy has been acknowledged by blue chip companies for quality training. Follow us on: https://www.facebook.com/jigsawacademy https://twitter.com/jigsawacademy http://jigsawacademy.com/
Views: 86846 Jigsaw Academy
Data Mining Using R (sometimes called data or knowledge discovery) is the process of analyzing data from different perspectives and summarizing it into useful information. Data Mining Certification Training Course Content : https://www.excelr.com/data-mining/ Introduction to Data Mining Tutorials : https://youtu.be/uNrg8ep_sEI What is Data Mining? Big data!!! Are you demotivated when your peers are discussing about data science and recent advances in big data. Did you ever think how Flip kart and Amazon are suggesting products for their customers? Do you know how financial institutions/retailers are using big data to transform themselves in to next generation enterprises? Do you want to be part of the world class next generation organisations to change the game rules of the strategy making and to zoom your career to newer heights? Here is the power of data science in the form of Data mining concepts which are considered most powerful techniques in big data analytics. Data Mining with R unveils underlying amazing patterns, wonderful insights which go unnoticed otherwise, from the large amounts of data. Data mining tools predict behaviours and future trends, allowing businesses to make proactive, unbiased and scientific-driven decisions. Data mining has powerful tools and techniques that answer business questions in a scientific manner, which traditional methods cannot answer. Adoption of data mining concepts in decision making changed the companies, the way they operate the business and improved revenues significantly. Companies in a wide range of industries such as Information Technology, Retail, Telecommunication, Oil and Gas, Finance, Health care are already using data mining tools and techniques to take advantage of historical data and to create their future business strategies. Data mining can be broadly categorized into two branches i.e. supervised learning and unsupervised learning. Unsupervised learning deals with identifying significant facts, relationships, hidden patterns, trends and anomalies. Clustering, Principle Component Analysis, Association Rules, etc., are considered unsupervised learning. Supervised learning deals with prediction and classification of the data with machine learning algorithms. Weka is most popular tool for supervised learning. Topics You Will Learn… Unsupervised learning: Introduction to datamining Dimension reduction techniques Principal Component Analysis (PCA) Singular Value Decomposition (SVD) Association rules / Market Basket Analysis / Affinity Filtering Recommender Systems / Recommendation Engine / Collaborative Filtering Network Analytics – Degree centrality, Closeness Centrality, Betweenness Centrality, etc. Cluster Analysis Hierarchical clustering K-means clustering Supervised learning: Overview of machine learning / supervised learning Data exploration methods Basic classification algorithms Decision trees classifier Random Forest K-Nearest Neighbours Bayesian classifiers: Naïve Bayes and other discriminant classifiers Perceptron and Logistic regression Neural networks Advanced classification algorithms Bayesian Networks Support Vector machines Model validation and interpretation Multi class classification problem Bagging (Random Forest) and Boosting (Gradient Boosted Decision Trees) Regression analysis Tools You Will Learn… R: R is a programming language to carry out complex statistical computations and data visualization. R is also open source software and backed by large community all over the world who are contributing to enhancing the capability. R has many advantages over other tools available in the market and it has been rated No.1 among the data scientist community. Mode of Trainings : E-Learning Online Training ClassRoom Training --------------------------------------------------------------------------- For More Info Contact :: Toll Free (IND) : 1800 212 2120 | +91 80080 09704 Malaysia: 60 11 3799 1378 USA: 001-608-218-3798 UK: 0044 203 514 6638 AUS: 006 128 520-3240 Email: [email protected] Web: www.excelr.com
Big Data is disrupting enterprises, and Hadoop is helping companies turn this challenge into opportunity. Explore different techniques that allow you to gain insight into your growing data and turn it into actionable decision making. Join us for an overview of how Big Data and Analytics work together, as well as the concepts of Machine Learning with Mahout. We will cover principles needed to drill down into your data through Data Mining, focusing on various techniques such as: Grouping / Clustering; Recommendation Systems; Prediction Modeling. Learn what these techniques are and how they can help you generate value for your organization. www.metascale.com #metascale
Views: 1304 MetaScale
http://www.sas.com/vdmml Boost analytical productivity and solve your most complex problems faster with a single, integrated in-memory environment that's both open and scalable. SAS VISUAL DATA MINING AND MACHINE LEARNING SAS Visual Data Mining and Machine Learning supports the end-to-end data mining and machine-learning process with a comprehensive, visual (and programming) interface that handles all tasks in the analytical life cycle. It suits a variety of users and there is no application switching. From data management to model development and deployment, everyone works in the same, integrated environment. http://www.sas.com/vdmml SUBSCRIBE TO THE SAS SOFTWARE YOUTUBE CHANNEL http://www.youtube.com/subscription_center?add_user=sassoftware ABOUT SAS SAS is the leader in analytics. Through innovative analytics, business intelligence and data management software and services, SAS helps customers at more than 75,000 sites make better decisions faster. Since 1976, SAS has been giving customers around the world THE POWER TO KNOW®. VISIT SAS http://www.sas.com CONNECT WITH SAS SAS ► http://www.sas.com SAS Customer Support ► http://support.sas.com SAS Communities ► http://communities.sas.com Facebook ► https://www.facebook.com/SASsoftware Twitter ► https://www.twitter.com/SASsoftware LinkedIn ► http://www.linkedin.com/company/sas Google+ ► https://plus.google.com/+sassoftware Blogs ► http://blogs.sas.com RSS ►http://www.sas.com/rss
Views: 5936 SAS Software
If you have questions or comments on the contents of this video, please email us at [email protected] There has been considerable change in the relationships between customers and companies. Customers are in control of the relationships with their vendors and are not afraid to switch to a new provider if they do not feel they are receiving the service they deserve. Companies now have the ability to know their customers and market to them on a personalized basis using data mining and predictive analytics technologies. Predictive Analytics unlock insights that enable companies to add new customers and grow their existing business by improving their understanding of what their customers want. It uncovers hidden insights in customer data to create more personalized customer experiences that win more business while reducing costs and increasing customer loyalty. Predictive Analytics enable the very sharpest competitive edge. They deliver powerful, unique, qualitative differentiation by providing your enterprise a proprietary source of business intelligence with which to compete in Operations, Customer or Threat & Fraud applications in your organization. A predictive model generated from your data taps into experience to which only your company is privy, since it is unique to your prospect list and to the product and marketing message to which your customers respond (both positively and negatively). Therefore, the model's intelligence and insights are outside the reaches of common knowledge, and the top prospects it flags compose a customized, proprietary contact list. View this informative webinar to learn more about how Predictive Analytics are making a difference in the insurance industry through focused target marketing, and more efficient fraudulent claim detection. We discuss a detailed use-case for a real-world insurance company examining how specific customer attributes were used as indicators for fraud prediction.
Views: 13544 LPA Software Solutions
In this Video, We will be discussing about the skills needed for data analyst and data scientist roles. The reason for making one video to discuss both data analyst and data scientist roles is because there are a lot things in common between both these two role. Data Analyst does a lot of descriptive analytics. On the other hand, Data Scientist also does descriptive analytics. But also data scientists do something called predictive analytics. So let's try to understand what Descriptive and Predictive analytics mean. Descriptive Analytics is all about analyzing the historical data to answer this particular question which is "WHAT HAS HAPPENED TILL NOW??". Predictive Analytics also involves analysis of historical data but, predictive analytics is mainly all about answering the question which is.. "WHAT WILL HAPPEN IN THE FUTURE??" Let's understand this with a simple example. I have sales data of XYZ company in a table format. As part of descriptive analytics, we can simply create a scatter chart so that we can quickly understand how the company has been performing in terms of sales in the previous years. Now let's look at predictive analytics. So now that we know how the company has been performing in the previous years, can we predict what's gonna happen to the sales in the coming years?.. Will the sales increase, or decrease or does it remain the same??.. If we are able to answer these questions, then it is called as predictive analytics. So coming back to the comparison of Data Analyst and Data Scientist roles, Now that we have some idea about the differences between the two roles, lets now look at skills needed for each of these two roles. Data Analysts should be good with Math and Statistics. They should be good with handling the data. -- This includes knowledge of ETL (or Extract Transform and Load) operations on data and experience working with popular ETL tools such as Informatica – PowerCenter,IBM – Infosphere Information Server, alteryx, Microsoft – SQL Server Integrated Services (SSIS), Talend Open Studio, SAS – Data Integration Studio ,SAP – BusinessObjects Data Integrator, QlikView Expressor or any other popular ETL tool. -- They should be comfortable in handling data from different sources and in different formats such as text, csv, tsv, excel, json, rdbms and others popular formats. -- They should have excellent knowledge of SQL (or Structured Query Language). Its a Bonus to have -- The knowledge of Big data tools and technologies to handle large data sets. -- NoSQL databases such as HBase, Cassandra and MongoDB. They should be expert in Analysing and Visualizing the data. -- They Should have experience working with popular data analysis and visualization packages in python and R such as numpy, scipy, pandas, matplotlib, ggplot and others. -- Experience with popular data analysis and visualization BI tools such as Tableau, Microsoft Power BI, SAP BI, SAS BI, Oracle BI, QlikView or any other popular BI tool They should have good communication and storytelling skills. Lets now look at the skills needed for data scientist role. Data scientist also does descriptive analytics just like data analysts. Apart from that, they also do predictive analytics. So as part of Descriptive analytics: Data Scientists should be excellent with Math and Statistics. Data scientists should be good with handling data -- So yes, they should have experience working with popular ETL frameworks. -- They should have excellent knowledge of SQL. -- Many companies expect data scientists to have mandatory knowledge of big data tools and technologies to work with large datasets and also to work with structured, semi-structured and unstructured data. -- Its good to have the knowledge of NoSQL databases such as HBase, Cassandra and MongoDB. They should be expert in Analysing and Visualizing the data. -- Experience working with popular data analysis and visualization packages in python and R. -- Experience with popular data analysis and visualization BI tools such as Tableau, Microsoft Power BI, SAP BI, SAS BI, Oracle BI, QlikView or any other popular BI tool. They should also have excellent communication and storytelling skills. And as part of predictive analytics, They should be good in using the techniques in artificial intelligence, data mining, machine learning, and statistical modeling to make future predictions using the historical data. Exposure to popular predictive analytics tools such as SAP Predictive analytics, Minitab, SAS Predictive Analytics, Alteryx Analytics, IBM predictive analytics or any other popular predictive analytics tool. They should have very good exposure to popular machine learning and deep learning packages available for Python and R such as scikit learn, tensorflow, theano,rpart, caret, randomForest, nnet, and other popular libraries.
Views: 61083 Art of Engineer
Retail Technology Fair EuroCIS 2015
Views: 118 icCube
Data mining, or knowledge discovery, is the computer-assisted process of digging through and analyzing enormous sets of data and then extracting the meaning of the data. Data mining tools predict behaviors and future trends, allowing business to make proactive, knowledge-driven decisions. Data mining tools can answer business questions that traditionally were too time consuming to resolve. They scour databases for hidden patterns, finding predictive information that experts may miss because it lies outside their expectations. Data mining derives its name from the similarities between searching for valuable information in a large database and mining a mountain for a vein of valuable ore. Both processes require either sifting through an immense amount of material, or intelligently probing it to find where the value resides. Data mining is primarily used today by companies with a strong consumer focus - retail, financial, communication, and marketing organizations. It enables these companies to determine relationships among "internal" factors such as price, product positioning, or staff skills, and "external" factors such as economic indicators, competition, and customer demographics. And, it enables them to determine the impact on sales, customer satisfaction, and corporate profits. Finally, it enables them to "drill down" into summary information to view detail transactional data.
Views: 360 OMICS International
GoldSpot Discoveries Inc is a technology platform using artificial intelligence and machine learning to make mining exploration more efficient. President and CEO Denis Laviolette provides an introduction to the company and explains that GoldSpot is the first and only AI company in mining. Lucrative deposits are growing harder to find and mining companies have collected considerable data in the pursuit of discovery. GoldSpot’s value proposition is that it uses AI and machine learning to find patterns in collected data that humans cannot locate. GoldSpot has raised $7.5 million as a private company and is already generating revenue. The company counts industry leaders like McEwen Mining Inc (TSE:MUX) (NYSE:MUX) (FRA:US8A) as clients and has an investment arm, Resource Quantamental. ************************ Check out our website: https://midasletter.com ************************ SUBSCRIBE to our YouTube: http://bit.ly/MidasLetterYoutube SUBSCRIBE to our 2nd YouTube Channel - Midas Letter Clips: https://bit.ly/2rtQzgy SUBSCRIBE to our Newsletter: http://bit.ly/MidasLetterNewsletter Download Our Podcast on iTunes: http://bit.ly/MidasLetterPodcast ************************ Follow Us on Twitter: http://bit.ly/MidasLetterTwitter Like Us on Instagram: http://bit.ly/MidasLetterInsta Like Us on Facebook: http://bit.ly/MidasLetterFacebook ************************ #WeedStocks #MidasLetter
Views: 448 Midas Letter RAW
Now that Azure Machine Learning Studio is setup, let’s begin an end-to-end data science project in Azure Machine Learning. We’ll choose the flight delay data, and use it to predict whether not a flight will be late on arrival based upon the flight’s circumstances. In this video we will begin our preliminary exploration into the dataset using Azure Machine Learning’s dataset module. In Part 4 we will cover: - introduction to projects - Exploring a data set using Azure ML - Building a data mining strategy -- Learn more about Data Science Dojo here: https://hubs.ly/H0hD1rd0 Watch the latest video tutorials here: https://hubs.ly/H0hD1LY0 See what our past attendees are saying here: https://hubs.ly/H0hD1Mk0 -- At Data Science Dojo, we believe data science is for everyone. Our in-person data science training has been attended by more than 4000+ employees from over 830 companies globally, including many leaders in tech like Microsoft, Apple, and Facebook. -- Like Us: https://www.facebook.com/datasciencedojo Follow Us: https://twitter.com/DataScienceDojo Connect with Us: https://www.linkedin.com/company/datasciencedojo Also find us on: Google +: https://plus.google.com/+Datasciencedojo Instagram: https://www.instagram.com/data_science_dojo Vimeo: https://vimeo.com/datasciencedojo
Views: 7344 Data Science Dojo
Florian Schwarz: "A warm welcome to productronica 2017. The special shows here are a big highlight – because that's where you can experience electronics manufacturing live!" "Founded in April 2017: the research fab Microelectronics Germany. This is where research capacities all over the country are bundled together and connected, to give the fab more weight internationally as a centre for microelectronics." "Ah, Dr. Olowinsky. Hello!" "Laser microwelding. What exactly are we looking at here?" Dr. Alexander Olowinsky: "Laser microwelding is an established method in electronics and precision engineering for creating electrical and mechanical connections.Here you can see a laser beam melting material – and that's what creates the connection. In this particular version, the laser head contains the beam guidance, beam forming and mechanical pressing combined, for a flexible manufacturing process." Florian Schwarz: "And what are the areas of application?" Dr. Alexander Olowinsky: "What you see here: classic battery technology, production of battery modules and of battery packs, production of electrical connections,all the way to printed circuit board technology, because we need to create connections there too." Florian Schwarz: "Dr. Olowinsky, thanks a lot!" Florian Schwarz: "From microelectronics to the special show devoted to hardware data mining.With me now is Ulf Oestermann, business developer at Fraunhofer IZM.Good morning!" FlorianSchwarz: "Mr. Oestermann, what's the connection between microelectronics and hardware data mining?" Ulf Oestermann: "The research fab Microelectronics Germany supposed to develop technologies and processes for the future. And they then have to be ported into mass production and scaled, so that they're ready to use there. That's exactly what hardware data mining is all about – showing what data records accumulate at what location in the individual process steps, and how robust they have to be in order to be used." Florian Schwarz: "So we're talking about 'digging' data? Can we take a closer look?" Ulf Oestermann: "Sure. No problem." Ulf Oestermann: "Based on the data matrix code, you can immediately establish when this subassembly was manufactured, at what temperature, and in what humidity, and then conclusions can be drawn about possible errors." Florian Schwarz: "I guess it helps save on resources – only having to replace individual components?" Ulf Oestermann: "It's showing how thick wire is bonded. A very, very large number of wires are needed to get a high current density in the contact." Florian Schwarz: "Mr. Oestermann, thanks very much for the tour. Hardware data mining. I'm going to the VDMA now to see what's being done with the data. And you? Back to work?" Ulf Oestermann: "That's right!" Florian Schwarz: "Ok - thanks. Ciao! We've just mined and collected the data. The data has to go somewhere, it has to be processed. And that brings me to the special show of the VDMA: "Smart-Data-Future Manufacturing." "With me now is Mr. Müller from the VDMA. I've just taken a look round your stand. There's a lot of data being generated here. What's going to be done with it?" Daniel Müller: "In the next stage, it's simply stored in various cloud systems, to make the long-term data actually usable. For models, for instance – like predictive maintenance." Florian Schwarz: "Smart Data. How do you see the future of that?" Daniel Müller: "A very exciting future topic is machinelearning - where companies try to make machines learn. So they can avoid errors, or correct them, all by themselves." Florian Schwarz: "Wow. Thank you very much, Mr. Müller! Smart Data Future Manufacturing – it's a topic we're going to keep a close eye on. Well, that's all from productronica 2017. I'm already looking forward to 2019! Goodbye!"
Views: 338 productronica
JOHANNESBURG (miningweekly.com) – Global professional services company Accenture is investing in a new Applied Intelligence Studio for Mining, in Johannesburg, which will combine the latest in data science and artificial intelligence technologies with deep industry knowledge for the development of new intelligent digital solutions that can help mining companies solve some of their most significant challenges.
Views: 40 CreamerMedia
In today's world we seem more lost despite the abundance of information. Tirthankar Dash, story teller & design thinker for leading businesses around the world gives us a cheat sheet to discover the inner story in each one of us, towards living a more fulfilled life Dash is the founder of Quantum360, a design firm that takes a human-centered, design-based approach to helping organisations innovate and design for a more human future. He is also the co-founder of StoryCompany, a company that serves as a search engine to find meaning at work and in life. StoryCo. is devoted to humanizing workplaces and helping each person explore themselves, their beliefs, behavior patterns and indeed their own story to arrive at their own unique answer to a fundamental question - “What makes my life meaningful?” This talk was given at a TEDx event using the TED conference format but independently organized by a local community. Learn more at http://ted.com/tedx
Views: 3700 TEDx Talks
Get more value from your data. Give more value to your business. Quiterian, the fastest and advanced Analytical BI platform, incorporates advanced analytic techniques and predictive analytics that allow extracting the maximum value of data by the users, easily and instantly. No need for being an expert to know not only what is happening and why but also predict what will happen. Helping companies to be more efficient and competitive.
Views: 465 Jose Pablo Fernandez
#CareerInDataScience | Know about what companies are looking for while hiring data scientist for data mining roles. Learn more about the job roles of a data scientist and why companies are setting up data science teams. Ullas Nambiar, VP-Technology & Head - Zenlabs, Zensar Technologies, shares his views on Data Science in this webinar jointly organized by Great Learning and Zensar Technologies. Ullas talks about the following: - The Art of Data Science - What a Data Scientist Does - What makes a good Data Scientist or a Data Science Team - Why are companies setting up Data Science Teams - How long does it take to become a Data Scientist Previously, Ullas was AVP of Data Science at Myntra, Head of Analytics at EMC and a Scientist at IBM Research. Ullas has over 15 years of experience in Technology Innovation and earned a Ph.D. in Computer Science from Arizona State University. Learn more about our analytics programs: PGP-Business Analytics: https://goo.gl/bMyueN PGP-Big Data Analytics: https://goo.gl/UoxJ1H Business Analytics Certificate Program: https://goo.gl/LXCytz #DataScience #DataMining #GreatLakes #GreatLearning About Great Learning: - Great Learning is an online and hybrid learning company that offers high-quality, impactful, and industry-relevant programs to working professionals like you. These programs help you master data-driven decision-making regardless of the sector or function you work in and accelerate your career in high growth areas like Data Science, Big Data Analytics, Machine Learning, Artificial Intelligence & more. - Watch the video to know ''Why is there so much hype around 'Artificial Intelligence'?'' https://www.youtube.com/watch?v=VcxpBYAAnGM - What is Machine Learning & its Applications? https://www.youtube.com/watch?v=NsoHx0AJs-U - Do you know what the three pillars of Data Science? Here explaining all about the pillars of Data Science: https://www.youtube.com/watch?v=xtI2Qa4v670 - Want to know more about the careers in Data Science & Engineering? Watch this video: https://www.youtube.com/watch?v=0Ue_plL55jU - For more interesting tutorials, don't forget to Subscribe our channel: https://www.youtube.com/user/beaconelearning?sub_confirmation=1 - Learn More at: https://www.greatlearning.in/ For more updates on courses and tips follow us on: - Google Plus: https://plus.google.com/u/0/108438615307549697541 - Facebook: https://www.facebook.com/GreatLearningOfficial/ - LinkedIn: https://www.linkedin.com/company/great-learning/ - Follow our Blog: https://www.greatlearning.in/blog/?utm_source=Youtube Great Learning has collaborated with the University of Texas at Austin for the PG Program in Artificial Intelligence and Machine Learning and with UT Austin McCombs School of Business for the PG Program in Analytics and Business Intelligence.
Views: 927 Great Learning
PROBLEM As per the current requirement of the project, the company is seeking the need of data analysts to do the analysis and help them make the decision process easier by comparing the graphs. Also, performing easy actions on the dashboard to enhance the decision-making process. The company have the MVP on the platform R Shiny using which they compare the various patient’s graph and draw conclusions from it. SOLUTION After analyzing the problem, we have decided to work on improving the visualization of the graphs by adding the colors and make them more readable. The purpose of this is to help the analyst to point out the differences easily and compare the graphs by just looking into it. This will help the analyst to make quick decisions in no time. Secondly, we have worked on providing the different measures to compare the images on parameters like Structural Similarity, Pixel Similarity, Shift Similarity and EMD (Earth mover’s distance). Each of these measures helps us to compare the two graphs and tell similarity in them by just looking into numbers. TOOLS AND TECHNOLOGIES We have used the R Studio and Shiny application to make the graphs visually better. Apart from this, we have used Python to create an algorithm to find out the different comparable parameters to understand similarity in the graphs. Comment and let us know what do you think!
Views: 19 SHILPA RANJAN
Make an animated explainer video for free at: http://www.rawshorts.com Now you create your own explainer videos and animated presentations for free. Raw Shorts is a free cloud based video builder that allows you to make awesome explanation videos for your business, website, startup video, pitch video, product launch, video resume, landing page video or anything else you could use an animated explainer video. Our free video templates and explainer video software will help you create presentation videos in an instant! It's never been easier to make an animated explainer video with outstanding production value and without the cost or hassle of hiring an expensive production company or animation studio. Wait no more! Our animation software is free to use. You can make an animated video today for your landing page, website, kickstarter video, indiegogo video, pitch video and more. Simply log on and select from thousands of animated icons, animated characters and free video templates for business to make the perfect web video for your business.
Views: 684 jojo20
By now, most industries recognize that "big data" and analytics can boost productivity, make processes more visible, and improve predictions of behavior. "Analytics will define the difference between the losers and winners going forward," says McKinsey Director Tim McGuire. In this video, he explains how to start thinking about analyzing data, and how to address the key strategic and organizational challenges of implementation by focusing on "the right data, the right modeling capability, and the right transformational methods to have your people act differently and make decisions differently." Learn how to understand the challenges and start crafting your plan with our special package, "Big data and advanced analytics" on McKinsey's site, http://bit.ly/McKAnalyticsVids. Join the conversation via the Twitter hashtag, #McKAnalytics (http://bit.ly/McKAnalytics).
Views: 35605 McKinsey & Company
Google Ventures, the investment arm of Google, has injected a sum of up to $10 million, as has In-Q-Tel -- which handles investments for the CIA and the wider intelligence network -- into a company called Recorded Future. The company describes its analytics as "the ultimate tool for open-source intelligence". Wired's defence analyst, Noah Schachtman, has a detailed report on the joint venture: "...it scours tens of thousands of websites, blogs and Twitter accounts to find the relationships between people, organizations, actions and incidents — both present and still-to-come. In a white paper, the company says its temporal analytics engine "goes beyond search" by "looking at the 'invisible links' between documents that talk about the same, or related, entities and events." The idea is to figure out for each incident who was involved, where it happened and when it might go down. Recorded Future then plots that chatter, showing online "momentum" for any given event." Recorded Future "continually scans thousands of news publications, blogs, niche sources, trade publications, government web sites, financial databases and more," according to it's portfolio. It sifts through millions of posts and conversations taking place on blogs, YouTube, Twitter and Amazon to "assemble actual real-time dossiers on people." It is also being integrated with Google Earth, which, as Schachtman points out in his piece, was seeded with In-Q-Tel/CIA investment. This integration will allow real time tracking of the locations of persons or groups as part of the overall intelligence dossier. Recorded Future takes in vast amounts of personal information such as employment changes, personal education and family relations. The video also shows categories covering pretty much everything else, including entertainment, music and movie releases, as well as other innocuous things like patent filings and product recalls.
Views: 6257 the1dutchmaster
http://www.pinkbarrio.com/blog/ Hola. "what is is" and myself are fed up with the sheep and their Facebook addiction. This video is about Facebook's Data Mining. Does anyone care about that? Why are many people so wrapped up in a company that is worth as much as USD $96 billion? Do people not realize that anything they do on Facebook is making more money for the 1% owners of that data-mining corporatist company? "what is is" also talks about Obama making the statement that he now supposedly for same-gender marriage, but not really. He is supposedly for same-gender marriage in the states where same-gender marriage is legal. Is anyone confused by the newspeak? Then Romney (not to be outdone) said he's for "gay adoption" but not for gay marriage. Okay. Then, it came out that Obama was "hastened" (forced) to make his statement after Biden apologized to him for coming out and supporting same-gender marriage before Obama did, and they were scrambling at the White House to clean up the mess from this. Biden felt it was a mistake for him to announce his support first, so he apologized to Mr Change We Can Believe In for saying that he was for gay marriage. Then Mr Change was "hastened" to say he is too. Purely election year politics to try to buy votes and get dinero/money from suckers who will fall for this. Lots of people are falling for it and gushing over Mr Change. They're ignoring that most of his policies are to the right of Bush. There's two words to describe those who are falling for: Gullible Sheep. Chau.---rosa barrio
Views: 764 ThePinkbarrio
Welcome to a Python for Finance tutorial series. In this series, we're going to run through the basics of importing financial (stock) data into Python using the Pandas framework. From here, we'll manipulate the data and attempt to come up with some sort of system for investing in companies, apply some machine learning, even some deep learning, and then learn how to back-test a strategy. I assume you know the fundamentals of Python. If you're not sure if that's you, click the fundamentals link, look at some of the topics in the series, and make a judgement call. If at any point you are stuck in this series or confused on a topic or concept, feel free to ask for help and I will do my best to help. https://pythonprogramming.net https://twitter.com/sentdex https://www.facebook.com/pythonprogramming.net/ https://plus.google.com/+sentdex
Views: 334653 sentdex
Paul Del Pozo Investment Group, LLC. is a South Florida based Real Estate Investment Company. He specializes in Buying, Selling, Rehabbing, and Flipping Wholesale properties. In his free time he lives in a fitness world building a health and bodybuilding background. What you’ll learn about in this episode: • How Paul went from being a bodybuilder and personal trainer to becoming a successful real estate investor • Paul’s process of obtaining and working leads, networking, and learning the fundamentals of wholesaling • Why Paul believes it’s important to develop your skills in finding leads before you do anything else • How Paul integrates technology into the operation of his real estate business • How Paul uses a MLS data program called Propstream to find lists and comps, and how it has changed his business • How Propstream allows you to filter lists based on different categories like equity, property characteristics and more • How Paul has found financial independence in the 3 1/2 years that he’s been working in real estate • Why getting into real estate has been a catalyst of self-improvement even in other areas of Paul’s life • Which markets Paul is working in now, and why he has been moving his focus more into cash flow • How the slogan “Flex and Flip” has become a cornerstone of Paul’s business philosophy and his professional calling card Resources: • http://REInvestorSummit.com/Data • http://REInvestorSummit.com/Machine • http://REInvestorSummit.com/Everywhere • http://REInvestorSummit.com/aof • http://REInvestorSummit.com/coaching Love the show? Subscribe, rate, review, and share! Here’s How » https://reinvestorsummit.com/how-to-subscribe-rate-our-podcast-5-stars-on-itunes/ Join the Real Estate Investor Summit Community: http://reinvestorsummit.com/ https://www.facebook.com/1000Houses/ https://twitter.com/mitch_stephen https://www.youtube.com/channel/UC3fkChxDhvYJyEdof5RhjAw https://www.linkedin.com/in/mitch-stephen-0b32491b/
Views: 151 Mitch Stephen
#PredictiveAnalytics | Learn the prediction of outcome or treatment of a case by legal courts of Appeals based on historical data using predictive analytics. Watch the video to understand analytics in legal using case study on real-life data set. How litigation analytics can flourish with the use of data mining and AI. Know more about our analytics Program: PGP- Business Analytics: https://goo.gl/V9RzVD PGP- Big Data Analytics: https://goo.gl/rRyjj4 Business Analytics Certification Program: https://goo.gl/7HPoUY #LegalTech #LegalAnalytics #GreatLearning #GreatLakes About Great Learning: - Great Learning is an online and hybrid learning company that offers high-quality, impactful, and industry-relevant programs to working professionals like you. These programs help you master data-driven decision-making regardless of the sector or function you work in and accelerate your career in high growth areas like Data Science, Big Data Analytics, Machine Learning, Artificial Intelligence & more. - Watch the video to know ''Why is there so much hype around 'Artificial Intelligence'?'' https://www.youtube.com/watch?v=VcxpBYAAnGM - What is Machine Learning & its Applications? https://www.youtube.com/watch?v=NsoHx0AJs-U - Do you know what the three pillars of Data Science? Here explaining all about the pillars of Data Science: https://www.youtube.com/watch?v=xtI2Qa4v670 - Want to know more about the careers in Data Science & Engineering? Watch this video: https://www.youtube.com/watch?v=0Ue_plL55jU - For more interesting tutorials, don't forget to Subscribe our channel: https://www.youtube.com/user/beaconelearning?sub_confirmation=1 - Learn More at: https://www.greatlearning.in/ For more updates on courses and tips follow us on: - Google Plus: https://plus.google.com/u/0/108438615307549697541 - Facebook: https://www.facebook.com/GreatLearningOfficial/ - LinkedIn: https://www.linkedin.com/company/great-learning/ - Follow our Blog: https://www.greatlearning.in/blog/?utm_source=Youtube Great Learning has collaborated with the University of Texas at Austin for the PG Program in Artificial Intelligence and Machine Learning and with UT Austin McCombs School of Business for the PG Program in Analytics and Business Intelligence.
Views: 1108 Great Learning
** Machine Learning with Python : https://www.edureka.co/machine-learning-certification-training ** This Edureka video on Decision Tree Algorithm in Python will take you through the fundamentals of decision tree machine learning algorithm concepts and its demo in Python. Below are the topics covered in this tutorial: 1. What is Classification? 2. Types of Classification 3. Classification Use Case 4. What is Decision Tree? 5. Decision Tree Terminology 6. Visualizing a Decision Tree 7 Writing a Decision Tree Classifier fro Scratch in Python using CART Algorithm Subscribe to our channel to get video updates. Hit the subscribe button above. Check out our Python Machine Learning Playlist: https://goo.gl/UxjTxm #decisiontree #decisiontreepython #machinelearningalgorithms - - - - - - - - - - - - - - - - - About the Course Edureka’s Machine Learning Course using Python is designed to make you grab the concepts of Machine Learning. The Machine Learning training will provide deep understanding of Machine Learning and its mechanism. As a Data Scientist, you will be learning the importance of Machine Learning and its implementation in python programming language. Furthermore, you will be taught Reinforcement Learning which in turn is an important aspect of Artificial Intelligence. You will be able to automate real life scenarios using Machine Learning Algorithms. Towards the end of the course, we will be discussing various practical use cases of Machine Learning in python programming language to enhance your learning experience. After completing this Machine Learning Certification Training using Python, you should be able to: Gain insight into the 'Roles' played by a Machine Learning Engineer Automate data analysis using python Describe Machine Learning Work with real-time data Learn tools and techniques for predictive modeling Discuss Machine Learning algorithms and their implementation Validate Machine Learning algorithms Explain Time Series and it’s related concepts Gain expertise to handle business in future, living the present - - - - - - - - - - - - - - - - - - - Why learn Machine Learning with Python? Data Science is a set of techniques that enables the computers to learn the desired behavior from data without explicitly being programmed. It employs techniques and theories drawn from many fields within the broad areas of mathematics, statistics, information science, and computer science. This course exposes you to different classes of machine learning algorithms like supervised, unsupervised and reinforcement algorithms. This course imparts you the necessary skills like data pre-processing, dimensional reduction, model evaluation and also exposes you to different machine learning algorithms like regression, clustering, decision trees, random forest, Naive Bayes and Q-Learning. For more information, Please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll free). Instagram: https://www.instagram.com/edureka_learning/ Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka
Views: 77363 edureka!
The overview of this video series provides an introduction to text analytics as a whole and what is to be expected throughout the instruction. It also includes specific coverage of: – Overview of the spam dataset used throughout the series – Loading the data and initial data cleaning – Some initial data analysis, feature engineering, and data visualization About the Series This data science tutorial introduces the viewer to the exciting world of text analytics with R programming. As exemplified by the popularity of blogging and social media, textual data if far from dead – it is increasing exponentially! Not surprisingly, knowledge of text analytics is a critical skill for data scientists if this wealth of information is to be harvested and incorporated into data products. This data science training provides introductory coverage of the following tools and techniques: – Tokenization, stemming, and n-grams – The bag-of-words and vector space models – Feature engineering for textual data (e.g. cosine similarity between documents) – Feature extraction using singular value decomposition (SVD) – Training classification models using textual data – Evaluating accuracy of the trained classification models Kaggle Dataset: https://www.kaggle.com/uciml/sms-spam-collection-dataset The data and R code used in this series is available here: https://code.datasciencedojo.com/datasciencedojo/tutorials/tree/master/Introduction%20to%20Text%20Analytics%20with%20R -- Learn more about Data Science Dojo here: https://hubs.ly/H0hz5_y0 Watch the latest video tutorials here: https://hubs.ly/H0hz61V0 See what our past attendees are saying here: https://hubs.ly/H0hz6-S0 -- At Data Science Dojo, we believe data science is for everyone. Our in-person data science training has been attended by more than 4000+ employees from over 800 companies globally, including many leaders in tech like Microsoft, Apple, and Facebook. -- Like Us: https://www.facebook.com/datasciencedojo Follow Us: https://twitter.com/DataScienceDojo Connect with Us: https://www.linkedin.com/company/datasciencedojo Also find us on: Google +: https://plus.google.com/+Datasciencedojo Instagram: https://www.instagram.com/data_science_dojo Vimeo: https://vimeo.com/datasciencedojo
Views: 74311 Data Science Dojo
#DataMining | What is Data Mining? What are the applications of Data Mining? In this course, you will learn the basic concepts and fundamentals of Data Mining and more. About the Speaker: Raghu Raman A V Raghu is a Big Data and AWS expert with over a decade of training and consulting experience in AWS, Apache Hadoop Ecosystem including Apache Spark. He has worked with global customers like IBM, Capgemini, HCL, Wipro to name a few as well as Bay Area startups in the US. #BigData #DataMining #GreatLakes #GreatLearning About Great Learning: - Great Learning is an online and hybrid learning company that offers high-quality, impactful, and industry-relevant programs to working professionals like you. These programs help you master data-driven decision-making regardless of the sector or function you work in and accelerate your career in high growth areas like Data Science, Big Data Analytics, Machine Learning, Artificial Intelligence & more. - Watch the video to know ''Why is there so much hype around 'Artificial Intelligence'?'' https://www.youtube.com/watch?v=VcxpBYAAnGM - What is Machine Learning & its Applications? https://www.youtube.com/watch?v=NsoHx0AJs-U - Do you know what the three pillars of Data Science? Here explaining all about the pillars of Data Science: https://www.youtube.com/watch?v=xtI2Qa4v670 - Want to know more about the careers in Data Science & Engineering? Watch this video: https://www.youtube.com/watch?v=0Ue_plL55jU - For more interesting tutorials, don't forget to Subscribe our channel: https://www.youtube.com/user/beaconelearning?sub_confirmation=1 - Learn More at: https://www.greatlearning.in/ For more updates on courses and tips follow us on: - Google Plus: https://plus.google.com/u/0/108438615307549697541 - Facebook: https://www.facebook.com/GreatLearningOfficial/ - LinkedIn: https://www.linkedin.com/company/great-learning/ - Follow our Blog: https://www.greatlearning.in/blog/?utm_source=Youtube Great Learning has collaborated with the University of Texas at Austin for the PG Program in Artificial Intelligence and Machine Learning and with UT Austin McCombs School of Business for the PG Program in Analytics and Business Intelligence.
Views: 345 Great Learning
#ArtificialNeuralNetwork | Beginners guide to how artificial neural network model works. Learn how neural network approaches the problem, why and how the process works in ANN, various ways errors can be used in creating machine learning models and ways to optimise the learning process. - Watch our new free Python for Data Science Beginners tutorial: https://greatlearningforlife.com/python - Visit https://greatlearningforlife.com our learning portal for 100s of hours of similar free high-quality tutorial videos on Python, R, Machine Learning, AI and other similar topics Know More about Great Lakes Analytics Programs: PG Program in Business Analytics (PGP-BABI): http://bit.ly/2f4ptdi PG Program in Big Data Analytics (PGP-BDA): http://bit.ly/2eT1Hgo Business Analytics Certificate Program: http://bit.ly/2wX42PD #ANN #MachineLearning #DataMining #NeuralNetwork About Great Learning: - Great Learning is an online and hybrid learning company that offers high-quality, impactful, and industry-relevant programs to working professionals like you. These programs help you master data-driven decision-making regardless of the sector or function you work in and accelerate your career in high growth areas like Data Science, Big Data Analytics, Machine Learning, Artificial Intelligence & more. - Watch the video to know ''Why is there so much hype around 'Artificial Intelligence'?'' https://www.youtube.com/watch?v=VcxpBYAAnGM - What is Machine Learning & its Applications? https://www.youtube.com/watch?v=NsoHx0AJs-U - Do you know what the three pillars of Data Science? Here explaining all about the pillars of Data Science: https://www.youtube.com/watch?v=xtI2Qa4v670 - Want to know more about the careers in Data Science & Engineering? Watch this video: https://www.youtube.com/watch?v=0Ue_plL55jU - For more interesting tutorials, don't forget to Subscribe our channel: https://www.youtube.com/user/beaconelearning?sub_confirmation=1 - Learn More at: https://www.greatlearning.in/ For more updates on courses and tips follow us on: - Google Plus: https://plus.google.com/u/0/108438615307549697541 - Facebook: https://www.facebook.com/GreatLearningOfficial/ - LinkedIn: https://www.linkedin.com/company/great-learning/ Great Learning has collaborated with the University of Texas at Austin for the PG Program in Artificial Intelligence and Machine Learning and with UT Austin McCombs School of Business for the PG Program in Analytics and Business Intelligence.
Views: 70557 Great Learning
Lesson - 01 Data Entry For Job In Excel In Hindi [ Company Product Entry ] https://youtu.be/z25Nk4-3nU0
Views: 1370912 Job Tech
In the final video in our Data Mining Fundamentals series, we conclude our discussion of different visualization techniques for data exploration with scatter plots and contour plots. We will define each plot, and share examples of when you can use each for your data mining. -- Learn more about Data Science Dojo here: https://hubs.ly/H0hCsC90 Watch the latest video tutorials here: https://hubs.ly/H0hCsPX0 See what our past attendees are saying here: https://hubs.ly/H0hCsQ00 -- At Data Science Dojo, we believe data science is for everyone. Our in-person data science training has been attended by more than 4000+ employees from over 830 companies globally, including many leaders in tech like Microsoft, Apple, and Facebook. -- Like Us: https://www.facebook.com/datasciencedojo Follow Us: https://plus.google.com/+Datasciencedojo Connect with Us: https://www.linkedin.com/company/datasciencedojo Also find us on: Google +: https://plus.google.com/+Datasciencedojo Instagram: https://www.instagram.com/data_science_dojo Vimeo: https://vimeo.com/datasciencedojo
Views: 3552 Data Science Dojo
This Decision Tree algorithm in Machine Learning tutorial video will help you understand all the basics of Decision Tree along with what is Machine Learning, problems in Machine Learning, what is Decision Tree, advantages and disadvantages of Decision Tree, how Decision Tree algorithm works with solved examples and at the end we will implement a Decision Tree use case/ demo in Python on loan payment prediction. This Decision Tree tutorial is ideal for both beginners as well as professionals who want to learn Machine Learning Algorithms. Below topics are covered in this Decision Tree Algorithm Tutorial: 1. What is Machine Learning? ( 02:25 ) 2. Types of Machine Learning? ( 03:27 ) 3. Problems in Machine Learning ( 04:43 ) 4. What is Decision Tree? ( 06:29 ) 5. What are the problems a Decision Tree Solves? ( 07:11 ) 6. Advantages of Decision Tree ( 07:54 ) 7. How does Decision Tree Work? ( 10:55 ) 8. Use Case - Loan Repayment Prediction ( 14:32 ) What is Machine Learning: Machine Learning is an application of Artificial Intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. Subscribe to our channel for more Machine Learning Tutorials: https://www.youtube.com/user/Simplilearn?sub_confirmation=1 Machine Learning Articles: https://www.simplilearn.com/what-is-artificial-intelligence-and-why-ai-certification-article?utm_campaign=Decision-Tree-Algorithm-With-Example-RmajweUFKvM&utm_medium=Tutorials&utm_source=youtube To gain in-depth knowledge of Machine Learning, check our Machine Learning certification training course: https://www.simplilearn.com/big-data-and-analytics/machine-learning-certification-training-course?utm_campaign=Decision-Tree-Algorithm-With-Example-RmajweUFKvM&utm_medium=Tutorials&utm_source=youtube #MachineLearningAlgorithms #Datasciencecourse #DataScience #SimplilearnMachineLearning #MachineLearningCourse - - - - - - - - About Simplilearn Machine Learning course: A form of artificial intelligence, Machine Learning is revolutionizing the world of computing as well as all people’s digital interactions. Machine Learning powers such innovative automated technologies as recommendation engines, facial recognition, fraud protection and even self-driving cars.This Machine Learning course prepares engineers, data scientists and other professionals with knowledge and hands-on skills required for certification and job competency in Machine Learning. - - - - - - - Why learn Machine Learning? Machine Learning is taking over the world- and with that, there is a growing need among companies for professionals to know the ins and outs of Machine Learning The Machine Learning market size is expected to grow from USD 1.03 Billion in 2016 to USD 8.81 Billion by 2022, at a Compound Annual Growth Rate (CAGR) of 44.1% during the forecast period. - - - - - - What skills will you learn from this Machine Learning course? By the end of this Machine Learning course, you will be able to: 1. Master the concepts of supervised, unsupervised and reinforcement learning concepts and modeling. 2. Gain practical mastery over principles, algorithms, and applications of Machine Learning through a hands-on approach which includes working on 28 projects and one capstone project. 3. Acquire thorough knowledge of the mathematical and heuristic aspects of Machine Learning. 4. Understand the concepts and operation of support vector machines, kernel SVM, naive Bayes, decision tree classifier, random forest classifier, logistic regression, K-nearest neighbors, K-means clustering and more. 5. Be able to model a wide variety of robust Machine Learning algorithms including deep learning, clustering, and recommendation systems - - - - - - - Who should take this Machine Learning Training Course? We recommend this Machine Learning training course for the following professionals in particular: 1. Developers aspiring to be a data scientist or Machine Learning engineer 2. Information architects who want to gain expertise in Machine Learning algorithms 3. Analytics professionals who want to work in Machine Learning or artificial intelligence 4. Graduates looking to build a career in data science and Machine Learning - - - - - - For more updates on courses and tips follow us on: - Facebook: https://www.facebook.com/Simplilearn - Twitter: https://twitter.com/simplilearn - LinkedIn: https://www.linkedin.com/company/simplilearn - Website: https://www.simplilearn.com Get the Android app: http://bit.ly/1WlVo4u Get the iOS app: http://apple.co/1HIO5J0
Views: 51873 Simplilearn
China has recently announced that they are banning bitcoin mining. This was a big announcement in the crypto-world and many Chinese bitcoin mining companies have since left China. Here are the 3 reasons why China made that decision, and how it affects the world. Like, share, subscribe, and comment on your thoughts and what topics you would like us to explain next! Join our channels! YouTube: http://bit.ly/thoughtmosphere Instagram: https://www.instagram.com/thoughtmosphere/ Facebook: https://www.facebook.com/Thoughtmosphereofficial Discord: https://discord.gg/d8tbYTK Patreon: https://www.patreon.com/thoughtmosphere About us: Thoughtmosphere is an educational channel that uses engaging visuals, stories, statistics, and attempted humor to explain the complex world around you and how it affects you, giving you greater insights into global affairs, so that you have something interesting to talk to your peers about. Sources: https://www.notion.so/thoughtmosphere/Source-China-banning-bitcoin-mining-c98e9dc7b05241db85a89aeed7462521 Done by the fine folks at www.gram.com.sg For business inquiries: [email protected] Additional Notes / Corrigendum : 1) National Development and Reform Commission (NDRC) [China’s macroeconomic planner] made a proposal for Bitcoin mining to be banned. It hasn’t been banned it’s merely a proposal put forward to be considered. The last such proposal from NDRC was raised in 2011, most of the industries/ companies to be banned are still operating. 2) China’s mining dominance has declined and is now believed to be 50% of world Hashrate thanks to rising electricity, the NDRC proposal and crackdown on corruption. This is positive as BTC becomes more decentralised and more secure in the long run. 3) China’s electricity rate is only $0.01kwh during the wet season for some dams and rises to $0.05-6kwh in the dry season. The cheapest electricity is actually in Iran at $0.0065KWh. 4) Overall estimated supply of gold is valued at 7T, China’s monetary supply currently stands at 3T – doubtful they’ll use gold to back their cryptocurrency, but then who would verify it's actually backed? If there was any kind of transparency to the gold backing the crypto supply it'd make it far harder to manipulate the markets "The United States can pay any debt it has because we can always print money to do that" - Alan Greenspan 5) The S9 a 2 year old SHA-256 (BTC ASIC) is actually the fastest ROI, many times faster than the newer S17 (@$0.03kwh). 6) Bitcoin mining is still a fraction of the power required for fiat processing. 7) Development on BTC is too slow and there would be alternative crypto with similar sovereignty and security but more scalable with lower transaction fees. However people are convinced that BTC has the first mover advantage and that layering is the solution – when we see SPEDN, Bakkt, Lightning Network, Liquid etc coming to light.
Views: 651 Thoughtmosphere
In-Database Data Mining Using Oracle Advanced Analytics Option for Classificaton using Insurance Use Case
Views: 5111 Charles Berger
Transportation companies and companies operating vehicle fleets have access to an abundance of data related to their vehicles. Is your organization using this data effectively? For more information visit http://www.bkd.com.
Views: 226 BKD CPAs & Advisors
THIS IS A EEON'S HOUSE PRODUCTION ONLY FROM EeoNs' CHANNEL ON THE NET Look we all Know that information is POWER, so stop allowing others that's right, allowing, others to seize and steal Your POWER. If someone tells you something that is unbelievable and they can supply no proof, put it in file 13 (the trash),, If you hear some new information, or someone says "guess what I just heard?", yet it is only gossip, You put that in file 13. If you hear on the news, "it is believed that such and such, such and such did such and such such and such", but they then follow by saying "we have few details", they are creating a narrative, telling you what they want you to conclude, you place that in file 13, and you stop listening to that channel.When people start placing this nonrecyclable junk, powerless information in file 13, that gives them power. now you may ask how is this power? Simply because the information retained is true, and we all know truth is not relative, there could only be one absolute truth, and when you have that one absolute truth, respecting that truth you are the most powerful person alive. Just think about it! Knowledge is your most valuable resource, do not waste it by allowing it to be contaminated with "Useless Bandini"- Remember "Bandini is the word for fertilizer"
Views: 722 EeoN
Here I explain the applications of CRISP-DM and Data Mining to the make believe company, Globalytics Week 1 Project Critiques are welcome as I'm striving to improve
Views: 47 Nicholas Coast