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Sentiment Analysis in 4 Minutes
 
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Link to the full Kaggle tutorial w/ code: https://www.kaggle.com/c/word2vec-nlp-tutorial/details/part-1-for-beginners-bag-of-words Sentiment Analysis in 5 lines of code: http://blog.dato.com/sentiment-analysis-in-five-lines-of-python I created a Slack channel for us, sign up here: https://wizards.herokuapp.com/ The Stanford Natural Language Processing course: https://class.coursera.org/nlp/lecture Cool API for sentiment analysis: http://www.alchemyapi.com/products/alchemylanguage/sentiment-analysis I recently created a Patreon page. If you like my videos, feel free to help support my effort here!: https://www.patreon.com/user?ty=h&u=3191693 Follow me: Twitter: https://twitter.com/sirajraval Facebook: https://www.facebook.com/sirajology Instagram: https://www.instagram.com/sirajraval/ Instagram: https://www.instagram.com/sirajraval/ Signup for my newsletter for exciting updates in the field of AI: https://goo.gl/FZzJ5w
Views: 97043 Siraj Raval
Natural Language Processing With Python and NLTK p.1 Tokenizing words and Sentences
 
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Natural Language Processing is the task we give computers to read and understand (process) written text (natural language). By far, the most popular toolkit or API to do natural language processing is the Natural Language Toolkit for the Python programming language. The NLTK module comes packed full of everything from trained algorithms to identify parts of speech to unsupervised machine learning algorithms to help you train your own machine to understand a specific bit of text. NLTK also comes with a large corpora of data sets containing things like chat logs, movie reviews, journals, and much more! Bottom line, if you're going to be doing natural language processing, you should definitely look into NLTK! Playlist link: https://www.youtube.com/watch?v=FLZvOKSCkxY&list=PLQVvvaa0QuDf2JswnfiGkliBInZnIC4HL&index=1 sample code: http://pythonprogramming.net http://hkinsley.com https://twitter.com/sentdex http://sentdex.com http://seaofbtc.com
Views: 435610 sentdex
C Programming for Machine Learning (LIVE)
 
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The ability to write implementations of machine learning algorithms in pure C allows developers to very efficiently manage memory allocation, concurrency, and control flow. That means fast implementations that can outperform preexisting models in other languages, including even (gasp) Python. It’s a useful skill to know and in this live stream I’ll use C and C-based Python tools like Cython + spaCy to develop some really fast natural language processing algorithms for text data. We’ll be able to tokenize, tag, normalize, vectorize, and dependency parse articles of text to derive valuable insights. No installation necessary, we'll do this together using Google Colab in the browser. Join me, there’s a lot to cover here! Code for this video: https://github.com/llSourcell/c_programming_for_machine_learning Please Subscribe! And like. And comment. That's what keeps me going. Want more education? Connect with me here: Twitter: https://twitter.com/sirajraval Facebook: https://www.facebook.com/sirajology instagram: https://www.instagram.com/sirajraval This video is apart of my Machine Learning Journey course: https://github.com/llSourcell/Machine_Learning_Journey More learning resources: https://pydata.org/berlin2016/schedule/presentation/51/ https://smerity.com/articles/2018/cython_for_high_and_low.html https://explosion.ai/blog/writing-c-in-cython https://spacy.io/api/cython https://medium.com/huggingface/100-times-faster-natural-language-processing-in-python-ee32033bdced Join us in the Wizards Slack channel: http://wizards.herokuapp.com/ Learn more about the School of AI: https://www.theschool.ai And please support me on Patreon: https://www.patreon.com/user?u=3191693 Signup for my newsletter for exciting updates in the field of AI: https://goo.gl/FZzJ5w
Views: 27451 Siraj Raval
C Programming Tutorial | Learn C programming | C language
 
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C Programming Language is the most popular computer language and most used programming language till now. It is very simple and elegant language. 1) This is by far the most comprehensive C Programming course you'll find here, or anywhere else. 2) This C Programming tutorial Series starts from the very basics and covers advanced concepts as we progress. This course breaks even the most complex applications down into simplistic steps. 3) It is aimed at complete beginners, and assumes that you have no programming experience whatsoever. 4) This C Programming tutorial Series uses Visual training method, offering users increased retention and accelerated learning. Every programmer should and must have learnt C whether it is a Java or C# expert, Because all these languages are derived from C. In this tutorial you will learn all the basic concept of C programming language. Every section in this tutorial is downloadable for offline learning. Topics will be added additional to the tutorial every week or the other which cover more topics and with advanced topics. This is we will Learn Data Types, Arithmetic, If, Switch, Ternary Operator, Arrays, For Loop, While Loop, Do While Loop, User Input, Strings, Functions, Recursion, File I/O, Exceptions, Pointers, Reference Operator , memory management, pre-processors and more. #Ctutorialforbeginners #Ctutorial #Cprogramming #Cprogrammingtutorial #Cbasicsforbeginners c tutorial for beginners. C programming tutorials for beginners. C Programming Language Tutorials Time: 00:12:35 - Lesson 2 - C programming introduction and first ‘hello world’ program Time: 00:25:45 - Lesson 3 - simple input & output ( printf, scanf, placeholder ) Time: 00:41:07 - Lesson 4: Comments Time: 00:44:32 - Lesson 5 - Variables and basic data types Time: 00:52:41 - Lesson 6 - simple math & operators Time: 1:00:00 - lesson 7 - if statements Time: 1:09:00 - lesson 8 - if else & nested if else Time: 1:20:00 - lesson 9 - the ternary (conditional) operator in C Time: 1:28:56 - Lesson 10 - Switch Statement in C Time: 1:43:35 - Lesson 11 - while loop Time: 1:52:24 - Lesson 12 - do while loop Time: 2:01:14 - Lesson 13 - for loop Time: 2:11:25 - Lesson 14 - functions in C Time: 2:22:54 - Lesson 15: Passing parameters and arguments in C Time: 2:31:40 - Lesson 16: Return values in functions Time: 2:41:33 - Lesson 17: scope rules in C Time: 2:51:08 - Lesson 18: Arrays in C Time: 3:02:28 - Lesson 19: Multidimentional arrays in C Time: 3:12:33 - Lesson 20: Passing Arrays as function arguments in C Time: 3:24:54 - Lesson 21: Pointers in C Time: 3:35:36 - Lesson 22: Array of pointers Time: 3:43:38 - Lesson 23: Passing pointers as function arguments Time: 3:57:44 - Lesson 24: Strings in C Time: 4:12:17 - Lesson 25: (struct) structures in C Time: 4:27:10 - Lesson 26: Unions in C -------------------Online Courses to learn---------------------------- Data Analytics with R Certification Training- http://bit.ly/2rSKHNP DevOps Certification Training - http://bit.ly/2T5P6bQ AWS Architect Certification Training - http://bit.ly/2PRHDeF Python Certification Training for Data Science - http://bit.ly/2BB3PV8 Java, J2EE & SOA Certification Training - http://bit.ly/2EKbwMK AI & Deep Learning with TensorFlow - http://bit.ly/2AeIHUR Big Data Hadoop Certification Training- http://bit.ly/2ReOl31 AWS Architect Certification Training - http://bit.ly/2EJhXjk Selenium Certification Training - http://bit.ly/2BFrfZs Tableau Training & Certification - http://bit.ly/2rODzSK Linux Administration Certification Training-http://bit.ly/2Gy9GQH ----------------------Follow--------------------------------------------- My Website - http://www.codebind.com My Blog - https://goo.gl/Nd2pFn My Facebook Page - https://goo.gl/eLp2cQ Google+ - https://goo.gl/lvC5FX Twitter - https://twitter.com/ProgrammingKnow Pinterest - https://goo.gl/kCInUp Text Case Converter - https://goo.gl/pVpcwL ------------------Facebook Links ---------------------------------------- http://fb.me/ProgrammingKnowledgeLearning/ http://fb.me/AndroidTutorialsForBeginners http://fb.me/Programmingknowledge http://fb.me/CppProgrammingLanguage http://fb.me/JavaTutorialsAndCode http://fb.me/SQLiteTutorial http://fb.me/UbuntuLinuxTutorials http://fb.me/EasyOnlineConverter
Views: 3605853 ProgrammingKnowledge
Twitter Sentiment Analysis - Natural Language Processing With Python and NLTK p.20
 
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Finally, the moment we've all been waiting for and building up to. A live test! We've decided to employ this classifier to the live Twitter stream, using Twitter's API. We've already covered how to do live Twitter API streaming, if you missed it, you can catch up here: http://pythonprogramming.net/twitter-api-streaming-tweets-python-tutorial/ After this, we output the findings to a text file, which we intend to graph! Playlist link: https://www.youtube.com/watch?v=FLZvOKSCkxY&list=PLQVvvaa0QuDf2JswnfiGkliBInZnIC4HL&index=1 sample code: http://pythonprogramming.net http://hkinsley.com https://twitter.com/sentdex http://sentdex.com http://seaofbtc.com
Views: 80086 sentdex
How to Make a Text Summarizer - Intro to Deep Learning #10
 
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I'll show you how you can turn an article into a one-sentence summary in Python with the Keras machine learning library. We'll go over word embeddings, encoder-decoder architecture, and the role of attention in learning theory. Code for this video (Challenge included): https://github.com/llSourcell/How_to_make_a_text_summarizer Jie's Winning Code: https://github.com/jiexunsee/rudimentary-ai-composer More Learning resources: https://www.quora.com/Has-Deep-Learning-been-applied-to-automatic-text-summarization-successfully https://research.googleblog.com/2016/08/text-summarization-with-tensorflow.html https://en.wikipedia.org/wiki/Automatic_summarization http://deeplearning.net/tutorial/rnnslu.html http://machinelearningmastery.com/text-generation-lstm-recurrent-neural-networks-python-keras/ Please subscribe! And like. And comment. That's what keeps me going. Join us in the Wizards Slack channel: http://wizards.herokuapp.com/ And please support me on Patreon: https://www.patreon.com/user?u=3191693 Follow me: Twitter: https://twitter.com/sirajraval Facebook: https://www.facebook.com/sirajology Instagram: https://www.instagram.com/sirajraval/ Instagram: https://www.instagram.com/sirajraval/ Signup for my newsletter for exciting updates in the field of AI: https://goo.gl/FZzJ5w
Views: 149910 Siraj Raval
Parser and Lexer — How to Create a Compiler part 1/5 — Converting text into an Abstract Syntax Tree
 
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In this tool-assisted education video I create a parser in C++ for a B-like programming language using GNU Bison. For the lexicographical analysis, a lexer is generated using re2c. This is part of a multi-episode series. In the next video, we will focus on optimization. Downloads: — https://github.com/bisqwit/compiler_series/tree/master/ep1 All the material associated with this episode can be downloaded here. Acknowledgements: — Picture: Processors :: Jason Rogers — Music¹: Aryol :: The Strategy Continues :: Kyohei Sada (converted into MIDI and played through OPL3 emulation through homebrew software) — Music²: Star Ocean :: Past Days :: Motoi Sakuraba (SPC-OPL3 conversion) — Music³: Rockman & Forte :: Museum :: Kirikiri-Chan and others (SPC-OPL3 conversion) — Music⁴: Famicom Tantei Club Part II: Ushiro ni Tatsu Shōjo :: Dean’s Room :: Kenji Yamamoto (SPC-OPL3 conversion), original composition: Bach's Invention № 15 — Music⁵: Aryol :: Arrest :: Kyohei Sada (SPC-OPL3 conversion) — Music⁶: Ren & Stimpy Show : Fire Dogs :: Main Theme :: Martin Gwynn Jones and others (SPC-OPL3 conversion) — Music⁷: Aryol :: Warmup :: Kyohei Sada (SPC-OPL3 conversion) — Music⁸: Energy Breaker :: Golden-Colored Wind :: Yukio Nakajima (SPC-OPL3 conversion) — Music⁹: Wonder Project J :: House :: Akihiko Mori (SPC-OPL3 conversion) — SFX: Mostly from YouTube Audio Library. Some are recorded from video games like The Guardian Legend, Lunar Ball, and Super Mario All-Stars. ¹ 00:37, ² 02:46 & 39:26, ³ 10:10, ⁴ 16:06, ⁵ 27:18, ⁶ 37:20, ⁷ 38:58 & 45:58, ⁸ 49:00, ⁹ 50:40 My links: Twitter: https://twitter.com/RealBisqwit Liberapay: https://liberapay.com/Bisqwit Steady: https://steadyhq.com/en/bisqwit Patreon: https://patreon.com/Bisqwit (Other options at https://bisqwit.iki.fi/donate.html) Twitch: https://twitch.tv/RealBisqwit Homepage: https://iki.fi/bisqwit/ You can contribute subtitles: https://www.youtube.com/timedtext_video?ref=share&v=eF9qWbuQLuw or to any of my videos: https://www.youtube.com/timedtext_cs_panel?tab=2&c=UCKTehwyGCKF-b2wo0RKwrcg ---Rant--- [9:35 PM] Bisqwit: Now uploading to YouTube. Within about 24 hours I will know if the rogue AI at YouTube slams the “limited or no advertising" stamp into it, or not. Actually, I only know if it does so *when* it does it. Then, I need to wait an additional 25 hours for YouTube staff to manually review it and clear the flag. If the flag does not appear, then it is possible that the bot just has not scanned it yet and I need to wait longer. Premature publication could mean that the bot will mark it after it has already been published, and then I will not receive any revenue for the first spike of views. It used to be 18 hours (since uploading that the bot does its evil deeds), but nowadays YT recommends waiting just 3 hours. We will see, we will see. #Bisqwit #Compiler #Tutorial
Views: 88629 Bisqwit
1.1: Introduction - Programming with Text
 
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Welcome to Programming from A to Z! "Programming from A to Z" is a course I teach at ITP (http://itp.nyu.edu). This playlist is anyone who would like to follow along online. Each week, I'll release videos on a new topic. Here is the course description. This course focuses on programming strategies and techniques behind procedural analysis and generation of text-based data. We'll explore topics ranging from evaluating text according to its statistical properties to the automated production of text with probabilistic methods to text visualization. Students will learn server-side and client-side JavaScript programming and develop projects that can be shared and interacted with online. There will be weekly homework assignments as well as a final project. Course url: http://shiffman.net/a2z/ Next Video: https://youtu.be/d3OcFexe9Ik Support this channel on Patreon: https://patreon.com/codingtrain Send me your questions and coding challenges!: https://github.com/CodingTrain/Rainbow-Topics Contact: https://twitter.com/shiffman GitHub Repo with all the info for Programming from A to Z: https://github.com/shiffman/A2Z-F16 Links discussed in this video: ITP from Tisch School of the Arts: https://tisch.nyu.edu/itp Influences and Inspiration for the Programming from A to Z class: Jackson Mac Low's Wikipedia Page: https://en.wikipedia.org/wiki/Jackson_Mac_Low Nick Montfort: http://nickm.com/ Allison Parrish: http://www.decontextualize.com/ Kate Compton's Tracery: https://github.com/galaxykate/tracery Addie Wagenknecht: http://www.placesiveneverbeen.com/ Lynn Cherny: http://www.ghostweather.com/bio.html Darius Kazemi: http://tinysubversions.com/ Eyeo Festival on Vimeo: https://vimeo.com/eyeofestival Source Code for the all Video Lessons: https://github.com/CodingTrain/Rainbow-Code p5.js: https://p5js.org/ Processing: https://processing.org For More Programming from A to Z videos: https://www.youtube.com/user/shiffman/playlists?shelf_id=11&view=50&sort=dd For More Coding Challenges: https://www.youtube.com/playlist?list=PLRqwX-V7Uu6ZiZxtDDRCi6uhfTH4FilpH Help us caption & translate this video! http://amara.org/v/V91D/
Views: 119370 The Coding Train
Coding Challenge #44.1: AFINN-111 Sentiment Analysis - Part 1
 
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This is Part 1 of a two-part Coding Challenge on Sentiment Analysis with the AFINN-111 word list. In this video, I explain what the AFINN-111 is and how to convert Tab Separated Values (.tsv) data into JSON data. This video is part of Session 8 of the "Programming from A to Z" ITP class. Link to Part 2: https://youtu.be/VV1JmMYceJw Course url: http://shiffman.net/a2z/ Support this channel on Patreon: https://patreon.com/codingtrain Send me your questions and coding challenges!: https://github.com/CodingTrain/Rainbow-Topics Contact: https://twitter.com/shiffman Links discussed in this video: AFINN: http://www2.imm.dtu.dk/pubdb/views/publication_details.php?id=6010 Node.js: https://nodejs.org/ Express.js: http://expressjs.com/ p5.js: https://p5js.org/ GitHub Repo with all the info for Programming from A to Z: https://github.com/shiffman/A2Z-F16 Source Code for the all Video Lessons: https://github.com/CodingTrain/Rainbow-Code For More Programming from A to Z videos: https://www.youtube.com/user/shiffman/playlists?shelf_id=11&view=50&sort=dd For More Coding Challenges: https://www.youtube.com/playlist?list=PLRqwX-V7Uu6ZiZxtDDRCi6uhfTH4FilpH Help us caption & translate this video! http://amara.org/v/0siX/
Views: 20210 The Coding Train
How to Do Sentiment Analysis - Intro to Deep Learning #3
 
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In this video, we'll use machine learning to help classify emotions! The example we'll use is classifying a movie review as either positive or negative via TF Learn in 20 lines of Python. Coding Challenge for this video: https://github.com/llSourcell/How_to_do_Sentiment_Analysis Ludo's winning code: https://github.com/ludobouan/pure-numpy-feedfowardNN See Jie Xun's runner up code: https://github.com/jiexunsee/Neural-Network-with-Python Tutorial on setting up an AMI using AWS: http://www.bitfusion.io/2016/05/09/easy-tensorflow-model-training-aws/ More learning resources: http://deeplearning.net/tutorial/lstm.html https://www.quora.com/How-is-deep-learning-used-in-sentiment-analysis https://gab41.lab41.org/deep-learning-sentiment-one-character-at-a-t-i-m-e-6cd96e4f780d#.nme2qmtll http://k8si.github.io/2016/01/28/lstm-networks-for-sentiment-analysis-on-tweets.html https://www.kaggle.com/c/word2vec-nlp-tutorial Please Subscribe! And like. And comment. That's what keeps me going. Join us in our Slack channel: wizards.herokuapp.com If you're wondering, I used style transfer via machine learning to add the fire effect to myself during the rap part. Please support me on Patreon: https://www.patreon.com/user?u=3191693 Follow me: Twitter: https://twitter.com/sirajraval Facebook: https://www.facebook.com/sirajology Instagram: https://www.instagram.com/sirajraval/ Instagram: https://www.instagram.com/sirajraval/ Signup for my newsletter for exciting updates in the field of AI: https://goo.gl/FZzJ5w
Views: 141021 Siraj Raval
Introduction to Natural Language Processing with Python - Asyncjs
 
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In this talk, Jess Bowden introduces the area of NLP (Natural Language Processing) and a basic introduction of its principles. She uses Python and some of its fundamental NLP packages, such as NLTK, to illustrate examples and topics, demonstrating how to get started with processing and analysing Natural Languages. She also looks at what NLP can be used for, a broad overview of the sub-topics, and how to get yourself started with a demo project. ▼ Links mentioned in the talk ▼ http://www.nltk.org/ https://github.com/yyuu/pyenv https://github.com/yyuu/pyenv-virtualenv http://jupyter.org/ ▼ Speaker ▼ https://twitter.com/jessicambowden ▼ Event ▼ This talk was part of AsyncJS in May (https://asyncjs.com/introduction-to-nlp-with-python/). ▼ Transcript ▼ https://blog.pusher.com/introduction-to-natural-language-processing-with-python/ ▼ Video by Pusher ▼ Pusher is a hosted service with APIs, developer tools and open source libraries that greatly simplify integrating real-time functionality into web and mobile applications. Pusher will automatically scale when required, removing all the pain of setting up and maintaining a secure, realtime infrastructure. Pusher is already trusted to do so by thousands of developers and companies like GitHub, MailChimp, the Financial Times, Buffer and many more. Getting started takes just a few seconds: simply go to pusher.com and create a free account. Happy hacking! ▼ More from Pusher ▼ Subscribe to Pusher: https://www.youtube.com/c/pusherrealtime?sub_confirmation=1 Asyncjs playlist: https://www.youtube.com/playlist?list=PL8xuokhAnn4pHB_R1KRz4_NEgPCUotyb8
Views: 27166 Pusher
KMeans Text Classification and Document Similarity with C# - Source Code Included
 
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Machine Learning from scratch with C# on Text Classification Blog: http://code-ai.mk/ One of the widely used natural language processing task in different business problems is “Text Classification”. The goal of text classification is to automatically classify the text documents into one or more defined categories. This is a short demonstration on how to cluster/group text documents.We'll use KMeans which is an unsupervised machine learning algorithm. On the video you can see I have collected a lot of Wikipedia articles on three categories and I want to classify them or rank them by similarity. First I process the text, then I create a word dictionary. Based on the word dictionary I will create another frequency dictionary which will contain the frequency at which every word occurs. I will need this to additionally clean up the text from words that do not bring any value/information to the clustering algorithm. Finally I would run KMeans using euclidean distance to find the centroids in the cluster of data. Similar documents would then be grouped together. The project is written from scratch in C#. Source code is also fully available on my blog or upon request. Blog: http://code-ai.mk/
Views: 457 Vanco Pavlevski
Building Bitcoin Software From Source Code
 
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Presentation Slides: http://averageradical.github.io/compile/#/ Send Tips directly to KevG @ bitcoin:1QDEf7xr33aHGPZUHg9WHQkyGLcYKXcv4i Much of the software associated with Bitcoin is open source, i.e. wallets, address generators, mining software, operating systems... Open source means the raw computer code is publicly available for scrutiny. Open source software is usually considered less buggy and more secure. One common obstacle with open source software is transforming it from the raw computer code to a program that runs on your phone, tablet, laptop, desktop. This process is called 'building from source'. This presentation seeks to demonstrate how to build from source several useful applications, with the ability to run these programs on multiple operating systems. Additionally, we will dive into the source code to make small changes prior to building, i.e. background color, edit text, etc... No software development experience necessary.
Views: 24726 Edge
How to recognize text from image with Python OpenCv OCR ?
 
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Recognize text from image using Python+ OpenCv + OCR. Buy me a coffee https://www.paypal.me/tramvm/5 if you think this is a helpful. Source code: http://www.tramvm.com/2017/05/recognize-text-from-image-with-python.html Relative videos: 1. ORM scanner: https://youtu.be/t66OAXI9mkw 2. Recognize answer sheet with mobile phone: https://youtu.be/82FlPaQ92OU 3. Recognize marked grid with USB camera: https://youtu.be/62P0c8YqVDk 4. Recognize answers sheet with mobile phone: https://youtu.be/xVLC4WdXvhE
Views: 101779 Tram Vo Minh
How to Build a Text Mining, Machine Learning Document Classification System in R!
 
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We show how to build a machine learning document classification system from scratch in less than 30 minutes using R. We use a text mining approach to identify the speaker of unmarked presidential campaign speeches. Applications in brand management, auditing, fraud detection, electronic medical records, and more.
Views: 163432 Timothy DAuria
How to Make a Simple Tensorflow Speech Recognizer
 
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In this video, we'll make a super simple speech recognizer in 20 lines of Python using the Tensorflow machine learning library. I go over the history of speech recognition research, then explain (and rap about) how we can build our own speech recognition system using the power of deep learning. The code for this video is here: https://github.com/llSourcell/tensorflow_speech_recognition_demo Mick's winning code: https://github.com/mickvanhulst/tf_chatbot_lotr The weekly challenge can be found at the end of the 'Make a Game Bot' video: https://www.youtube.com/watch?v=mGYU5t8MO7s More learning resources: https://www.superlectures.com/iscslp2014/tutorial-4-deep-learning-for-speech-generation-and-synthesis http://andrew.gibiansky.com/blog/machine-learning/speech-recognition-neural-networks/ https://www.youtube.com/watch?v=LFDU2GX4AqM https://www.youtube.com/watch?v=g-sndkf7mCs Please subscribe! And like and comment. That's what keeps me going. And please support me on Patreon! I don't work for anyone, although I did make a one-off video for OpenAI because I love them: https://www.patreon.com/user?u=3191693 Follow me: Twitter: https://twitter.com/sirajraval Facebook: https://www.facebook.com/sirajology Instagram: https://www.instagram.com/sirajraval/ Instagram: https://www.instagram.com/sirajraval/ Signup for my newsletter for exciting updates in the field of AI: https://goo.gl/FZzJ5w
Views: 188903 Siraj Raval
Coding Challenge #40.3: TF-IDF
 
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In part 3 of the Word Counting Coding Challenge, I implement an algorithm known as TF-IDF (Term Frequency – Inverse Document Frequency). The algorithm scores each word's relevance for a given document based on its frequency in one document relative to all others in a corpus. This is one possible methods for keyword generation. http://shiffman.net/a2z/text-analysis/ Course url: http://shiffman.net/a2z/ Support this channel on Patreon: https://patreon.com/codingtrain Send me your questions and coding challenges!: https://github.com/CodingTrain/Rainbow-Topics Contact: https://twitter.com/shiffman GitHub Repo with all the info for Programming from A to Z: https://github.com/shiffman/A2Z-F16 Links discussed in this video: ITP from Tisch School of the Arts: https://tisch.nyu.edu/itp TD-IDF on Wikipedia: https://en.wikipedia.org/wiki/Tf%E2%80%93idf Source Code for the all Video Lessons: https://github.com/CodingTrain/Rainbow-Code p5.js: https://p5js.org/ Processing: https://processing.org For More Programming from A to Z videos: https://www.youtube.com/user/shiffman/playlists?shelf_id=11&view=50&sort=dd For More Coding Challenges: https://www.youtube.com/playlist?list=PLRqwX-V7Uu6ZiZxtDDRCi6uhfTH4FilpH Help us caption & translate this video! http://amara.org/v/XWYv/
Views: 29521 The Coding Train
Regular Expressions (Regex) Tutorial: How to Match Any Pattern of Text
 
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In this regular expressions (regex) tutorial, we're going to be learning how to match patterns of text. Regular expressions are extremely useful for matching common patterns of text such as email addresses, phone numbers, URLs, etc. Almost every programming language has a regular expression library, so learning regular expressions with not only help you with finding patterns in your text editors, but also you'll be able to use these programming libraries to search for patterns programmatically as well. Let's get started... The code from this video can be found at: https://github.com/CoreyMSchafer/code_snippets/tree/master/Regular-Expressions Python Regex Tutorial: https://youtu.be/K8L6KVGG-7o If you enjoy these videos and would like to support my channel, I would greatly appreciate any assistance through my Patreon account: https://www.patreon.com/coreyms Or a one-time contribution through PayPal: https://goo.gl/649HFY If you would like to see additional ways in which you can support the channel, you can check out my support page: http://coreyms.com/support/ Equipment I use and books I recommend: https://www.amazon.com/shop/coreyschafer You can find me on: My website - http://coreyms.com/ Facebook - https://www.facebook.com/CoreyMSchafer Twitter - https://twitter.com/CoreyMSchafer Google Plus - https://plus.google.com/+CoreySchafer44/posts Instagram - https://www.instagram.com/coreymschafer/
Views: 193532 Corey Schafer
Whatsapp chat sentiment analysis in R | Sudharsan
 
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Whatsapp Chat Sentiment analysis using R programming! Subscribe to my channel for new and cool tutorials. You can also reach out to me on twitter: https://twitter.com/sudharsan1396 Code for this video: https://github.com/sudharsan13296/Whatsapp-analytics
Text Classification - Natural Language Processing With Python and NLTK p.11
 
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Now that we understand some of the basics of of natural language processing with the Python NLTK module, we're ready to try out text classification. This is where we attempt to identify a body of text with some sort of label. To start, we're going to use some sort of binary label. Examples of this could be identifying text as spam or not, or, like what we'll be doing, positive sentiment or negative sentiment. Playlist link: https://www.youtube.com/watch?v=FLZvOKSCkxY&list=PLQVvvaa0QuDf2JswnfiGkliBInZnIC4HL&index=1 sample code: http://pythonprogramming.net http://hkinsley.com https://twitter.com/sentdex http://sentdex.com http://seaofbtc.com
Views: 99147 sentdex
Jason Kessler - Using Scattertext and the Python NLP Ecosystem for Text Visualization
 
34:31
Description Scattertext is a Python package that lets you compare and contrast how words are used differently in two types of documents, producing interactive, Javascript-based visualizations that can easily be embedded into Jupyter Notebooks. Using spaCy and Empath, Scattertext can also show how emotional states and words relating to a particular topic differ. Abstract Notebooks and presentation for this talk are available from https://github.com/JasonKessler/Scattertext-PyData. Motivation and introduction -What's the matter with word clouds? -How to read a plot made by Scattertext How to make your own plots -Preparing a Pandas data frame with your data set -Plotting with Scattertext, and fine tuning plots for interpretability and speed Scattertext and the Python NLP ecosystem -Visualizing emotions using Empath. -Using word vectors from spaCy and elsewhere see how topic-specific language differs. -Visualizing topic models from scikit-learn. Links -Source code for the package is hosted on Github at github.com/JasonKessler/scattertext. -For more information, please see the paper which will appear as a 2017 ACL Demo at https://arxiv.org/abs/1703.00565. www.pydata.org PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. PyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.
Views: 3980 PyData
What is a HashTable Data Structure - Introduction to Hash Tables , Part 0
 
07:37
This tutorial is an introduction to hash tables. A hash table is a data structure that is used to implement an associative array. This video explains some of the basic concepts regarding hash tables, and also discusses one method (chaining) that can be used to avoid collisions. Wan't to learn C++? I highly recommend this book http://amzn.to/1PftaSt Donate http://bit.ly/17vCDFx
Views: 774426 Paul Programming
C++ mini-project ATM & Banking ✔
 
11:55
Project developed using C & C++ languages and handled data using files. Source Code: https://github.com/rohithvutnoor/Project_ATM . Video to Audio: https://www.youtube.com/watch?v=ZUzeO... Text to Audio: http://www.fromtexttospeech.com/ Due to copyrights the entire background music was removed. Dev C++: http://sourceforge.net/projects/orwel... Java Project EditNote : https://www.youtube.com/watch?v=YaxWhZB9CYw
Views: 97314 Rohith Vutnoor
How to Setup Atom For C / C++ Development on Windows 10
 
13:04
This is a Instructional Video on how to compile C and C ++ programs in Atom Text Editor, one of the best open source text editors. Links shown in the video: Atom Text Editor: https://atom.io/ MinGW: http://www.mingw.org/ Gpp-compiler package: https://atom.io/packages/gpp-compiler Atom is opensource source code and text editor. Atom can be installed on Windows, Linux and OS X. Atom supports plugins written in Node.js and has embedded Git source control. Atom is developed by GitHub. Atom is build using web technologies and used as a desktop application. In this post we will see how to install Atom editor on your Windows 10 system. -------------------Online Courses to learn---------------------------- Blockchain Course - http://bit.ly/2Mmzcv0 Big Data Hadoop Course - http://bit.ly/2MV97PL Java - https://bit.ly/2H6wqXk C++ - https://bit.ly/2q8VWl1 AngularJS - https://bit.ly/2qebsLu Python - https://bit.ly/2Eq0VSt C- https://bit.ly/2HfZ6L8 Android - https://bit.ly/2qaRSAS Linux - https://bit.ly/2IwOuqz AWS Certified Solutions Architect - https://bit.ly/2JrGoAF Modern React with Redux - https://bit.ly/2H6wDtA MySQL - https://bit.ly/2qcF63Z ----------------------Follow--------------------------------------------- My Website - http://www.codebind.com My Blog - https://goo.gl/Nd2pFn My Facebook Page - https://goo.gl/eLp2cQ Google+ - https://goo.gl/lvC5FX Twitter - https://twitter.com/ProgrammingKnow Pinterest - https://goo.gl/kCInUp Text Case Converter - https://goo.gl/pVpcwL -------------------------Stuff I use to make videos ------------------- Stuff I use to make videos Windows notebook – http://amzn.to/2zcXPyF Apple MacBook Pro – http://amzn.to/2BTJBZ7 Ubuntu notebook - https://amzn.to/2GE4giY Desktop - http://amzn.to/2zct252 Microphone – http://amzn.to/2zcYbW1 notebook mouse – http://amzn.to/2BVs4Q3 ------------------Facebook Links ---------------------------------------- http://fb.me/ProgrammingKnowledgeLearning/ http://fb.me/AndroidTutorialsForBeginners http://fb.me/Programmingknowledge http://fb.me/CppProgrammingLanguage http://fb.me/JavaTutorialsAndCode http://fb.me/SQLiteTutorial http://fb.me/UbuntuLinuxTutorials http://fb.me/EasyOnlineConverter
Views: 51606 ProgrammingKnowledge
Naive Bayes w/ JAVA - Tutorial 01
 
16:12
Website + download source code @ http://www.zaneacademy.com
Views: 5863 zaneacademy
Introduction to Data Science with R - Data Analysis Part 1
 
01:21:50
Part 1 in a in-depth hands-on tutorial introducing the viewer to Data Science with R programming. The video provides end-to-end data science training, including data exploration, data wrangling, data analysis, data visualization, feature engineering, and machine learning. All source code from videos are available from GitHub. NOTE - The data for the competition has changed since this video series was started. You can find the applicable .CSVs in the GitHub repo. Blog: http://daveondata.com GitHub: https://github.com/EasyD/IntroToDataScience I do Data Science training as a Bootcamp: https://goo.gl/OhIHSc
Views: 940477 David Langer
Why You Should Do Text Analysis in Python (Even if You Don't Want to) - Bhargav Srinivasa Desikan
 
48:31
PyData LA 2018 The explosion in Artificial Intelligence and Machine Learning is unprecedented now - and text analysis is likely the most easily accessible and understandable part of this. And with python, it is crazy easy to do this - python has been used as a parsing language forever, and with the rich set of NLP, ML and Computational Linguistic tools, it's worth doing text analysis even if you don't want to. --- www.pydata.org PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. PyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.
Views: 832 PyData
How to Install Codeblocks IDE on Windows 10 with Compilers ( GCC , G++)
 
07:10
In this video I am going to show How to Install Codeblocks IDE on Windows 10 with Compilers. We will see how to install MinGw compiler with code blocks. ( GCC , G++) -------------------Online Courses to learn---------------------------- Data Analytics with R Certification Training- http://bit.ly/2rSKHNP DevOps Certification Training - http://bit.ly/2T5P6bQ AWS Architect Certification Training - http://bit.ly/2PRHDeF Python Certification Training for Data Science - http://bit.ly/2BB3PV8 Java, J2EE & SOA Certification Training - http://bit.ly/2EKbwMK AI & Deep Learning with TensorFlow - http://bit.ly/2AeIHUR Big Data Hadoop Certification Training- http://bit.ly/2ReOl31 AWS Architect Certification Training - http://bit.ly/2EJhXjk Selenium Certification Training - http://bit.ly/2BFrfZs Tableau Training & Certification - http://bit.ly/2rODzSK Linux Administration Certification Training-http://bit.ly/2Gy9GQH ----------------------Follow--------------------------------------------- My Website - http://www.codebind.com My Blog - https://goo.gl/Nd2pFn My Facebook Page - https://goo.gl/eLp2cQ Google+ - https://goo.gl/lvC5FX Twitter - https://twitter.com/ProgrammingKnow Pinterest - https://goo.gl/kCInUp Text Case Converter - https://goo.gl/pVpcwL ------------------Facebook Links ---------------------------------------- http://fb.me/ProgrammingKnowledgeLearning/ http://fb.me/AndroidTutorialsForBeginners http://fb.me/Programmingknowledge http://fb.me/CppProgrammingLanguage http://fb.me/JavaTutorialsAndCode http://fb.me/SQLiteTutorial http://fb.me/UbuntuLinuxTutorials http://fb.me/EasyOnlineConverter Best C++ Complier : How to Install Code:Block in Windows 10 , Windows c++ - Setting up MingW and Code::Blocks in Windows 10 64 Searches related to install codeblocks on windows 10 how to install codeblocks on mac download codeblocks for windows download codeblocks for windows 10 64 bit download codeblocks for windows 8 install gcc windows
Views: 361600 ProgrammingKnowledge
Hello World - Machine Learning Recipes #1
 
06:53
Six lines of Python is all it takes to write your first machine learning program! In this episode, we'll briefly introduce what machine learning is and why it's important. Then, we'll follow a recipe for supervised learning (a technique to create a classifier from examples) and code it up. Follow https://twitter.com/random_forests for updates on new episodes! Subscribe to the Google Developers: http://goo.gl/mQyv5L - Subscribe to the brand new Firebase Channel: https://goo.gl/9giPHG And here's our playlist: https://goo.gl/KewA03
Views: 1867544 Google Developers
Introduction - Learn Python for Data Science #1
 
06:55
Welcome to the 1st Episode of Learn Python for Data Science! This series will teach you Python and Data Science at the same time! In this video we install Python and our text editor (Sublime Text), then build a gender classifier using the sci-kit learn library in just about 10 lines of code. Please subscribe & share this video if you liked it! The code for this video is here: https://github.com/llSourcell/gender_classification_challenge I created a Slack channel for us, sign up here: https://wizards.herokuapp.com/ Download Python here: https://www.python.org/downloads/ Download Sublime Text here: https://www.sublimetext.com/3 Some Great simple sci-kit learn examples here: https://github.com/chribsen/simple-machine-learning-examples and the official scikit website: http://scikit-learn.org/ Highly recommend this online book as supplementary reading material: https://learnpythonthehardway.org/book/ Wondering when to use which model? This chart helps, but keep in mind deep neural nets outperform pretty much any model given enough data and computing power. so use these when you don't have access to loads of data and compute: http://scikit-learn.org/stable/tutorial/machine_learning_map/ Thank you guys for watching! Subscribe, like, and comment! That's what keeps me going. Feel free to support me on Patreon: https://www.patreon.com/user?u=3191693 Follow me: Twitter: https://twitter.com/sirajraval Facebook: https://www.facebook.com/sirajology Instagram: https://www.instagram.com/sirajraval/ Instagram: https://www.instagram.com/sirajraval/ Signup for my newsletter for exciting updates in the field of AI: https://goo.gl/FZzJ5w
Views: 477798 Siraj Raval
Set Up C++ Development With Visual Studio Code on Windows 10 (VS Code)
 
23:36
In this video I am going to show, How to Set Up C++ Development With Visual Studio Code on Windows 10. We will use MinGW with VS code as our compiler and debugging tool. So First I will show How to install mingw. The we will see how to create, build and compile our first C++ Program on VScode. With an updated VS Code you can do it in the following manner: Hit (Ctrl+P) and type: ext install cpptools Open a folder (Ctrl+K & Ctrl+O) and create a new file inside the folder with the extension .cpp (ex: main.cpp): Type in your code and hit save. Press (Ctrl+Shift+P and type, Configure task runner and then select other at the bottom of the list. { "version": "2.0.0", "tasks": [ { "label": "build hello world", "type": "shell", "command": "g++", "args": [ "-g", "helloworld.cpp" ], "group": { "kind": "build", "isDefault": true } } ] } Hit (Ctrl+Shift+B to run Build task. This will create the .obj and .exe files for the project. For debugging the project, Hit F5 and select C++(Windows). In launch.json file, edit the following line and save the file: Below is an example using the MinGW GDB debugger: { "version": "0.2.0", "configurations": [ { "name": "(gdb) Launch", "type": "cppdbg", "request": "launch", "program": "${workspaceFolder}/a.exe", "args": [], "stopAtEntry": false, "cwd": "${workspaceFolder}", "environment": [], "externalConsole": true, "MIMode": "gdb", "miDebuggerPath": "C:\\mingw\\bin\\gdb.exe", "setupCommands": [ { "description": "Enable pretty-printing for gdb", "text": "-enable-pretty-printing", "ignoreFailures": true } ], "preLaunchTask": "build hello world" } ] } Hit F5. -------------------Online Courses to learn---------------------------- Data Analytics with R Certification Training- http://bit.ly/2rSKHNP DevOps Certification Training - http://bit.ly/2T5P6bQ AWS Architect Certification Training - http://bit.ly/2PRHDeF Python Certification Training for Data Science - http://bit.ly/2BB3PV8 Java, J2EE & SOA Certification Training - http://bit.ly/2EKbwMK AI & Deep Learning with TensorFlow - http://bit.ly/2AeIHUR Big Data Hadoop Certification Training- http://bit.ly/2ReOl31 AWS Architect Certification Training - http://bit.ly/2EJhXjk Selenium Certification Training - http://bit.ly/2BFrfZs Tableau Training & Certification - http://bit.ly/2rODzSK Linux Administration Certification Training-http://bit.ly/2Gy9GQH ----------------------Follow--------------------------------------------- My Website - http://www.codebind.com My Blog - https://goo.gl/Nd2pFn My Facebook Page - https://goo.gl/eLp2cQ Google+ - https://goo.gl/lvC5FX Twitter - https://twitter.com/ProgrammingKnow Pinterest - https://goo.gl/kCInUp Text Case Converter - https://goo.gl/pVpcwL ------------------Facebook Links ---------------------------------------- http://fb.me/ProgrammingKnowledgeLearning/ http://fb.me/AndroidTutorialsForBeginners http://fb.me/Programmingknowledge http://fb.me/CppProgrammingLanguage http://fb.me/JavaTutorialsAndCode http://fb.me/SQLiteTutorial http://fb.me/UbuntuLinuxTutorials http://fb.me/EasyOnlineConverter
Views: 211498 ProgrammingKnowledge
9.1: What is Firebase? (Database as a Service) - Programming with Text
 
05:56
In this video, I introduce the concept of "Database as a Service" (DBaaS). I discuss how you can store data in a web application written with client-side JavaScript only. This is the first video in a tutorial series about Firebase. This video is part of the "Programming from A to Z" ITP course. Next video: https://youtu.be/7lEU1UEw3YI Course url: http://shiffman.net/a2z/firebase/ Support this channel on Patreon: https://patreon.com/codingtrain Send me your questions and coding challenges!: https://github.com/CodingTrain/Rainbow-Topics Contact: https://twitter.com/shiffman GitHub Repo with all the info for Programming from A to Z: https://github.com/shiffman/A2Z-F16 Links discussed in this video: Firebase: https://firebase.google.com/ https://firebase.google.com/docs/database/web/read-and-write Source Code for the all Video Lessons: https://github.com/CodingTrain/Rainbow-Code For More Programming from A to Z videos: https://www.youtube.com/user/shiffman/playlists?shelf_id=11&view=50&sort=dd For More Coding Challenges: https://www.youtube.com/playlist?list=PLRqwX-V7Uu6ZiZxtDDRCi6uhfTH4FilpH Help us caption & translate this video! http://amara.org/v/1IZm/
Views: 83357 The Coding Train
CppCon 2018: Bob Steagall “Fast Conversion From UTF-8 with C++, DFAs, and SSE Intrinsics”
 
01:09:40
http://CppCon.org — Presentation Slides, PDFs, Source Code and other presenter materials are available at: https://github.com/CppCon/CppCon2018 — UTF-8 is taking on an increasingly important role in text processing. Many applications require the conversion of UTF-8 to UTF-16 or UTF-32, but typical conversion algorithms are sub-optimal. This talk will describe a fast, correct, DFA-based approach to UTF-8 conversion that requires only three simple lookup tables and a small amount of straightforward C++ code. We'll begin with a quick review UTF-8 and its relation to UTF-16 and UTF-32, as well as the concept of code units and code points. Next, we'll look at the layout of bits within a UTF-8 byte sequence, and from that, show a simple algorithm for converting from UTF-8 to UTF-32. Along the way will be a definition of overlong and invalid byte sequences. Following that will be a discussion of how to construct a DFA to perform the same operations as the simple algorithm. We'll then look at code for the DFA traversal underlying the basic conversion algorithm, and how to gain an additional performance boost by using SSE intrinsics. Finally, we'll compare the performance of this approach to several commonly-available implementations on Windows and Linux, and show how it's possible to do significantly faster conversions. — Bob Steagall, KEWB Computing CppCon Poster Chair I've been working in C++ since discovering the second edition of The C++ Programming Language in a college bookstore in 1992. The majority of my career has been spent in medical imaging, where I led teams building applications for functional MRI and CT-based cardiac visualization. After a brief detour through the world of DNS and analytics, I'm now working in the area of distributed stream processing. I'm a relatively new member of the C++ Standardization Committee, and launched a blog earlier this year to write about C++ and related topics. I hold BS and MS degrees in Physics, and I'm an avid cyclist when weather permits. — Videos Filmed & Edited by Bash Films: http://www.BashFilms.com
Views: 5426 CppCon
YOLO Object Detection (TensorFlow tutorial)
 
21:51
You Only Look Once - this object detection algorithm is currently the state of the art, outperforming R-CNN and it's variants. I'll go into some different object detection algorithm improvements over the years, then dive into YOLO theory and a programmatic implementation using Tensorflow! Code for this video: https://github.com/llSourcell/YOLO_Object_Detection Please Subscribe! And like. And comment. That's what keeps me going. Want more inspiration & education? Follow me: Twitter: https://twitter.com/sirajraval Facebook: https://www.facebook.com/sirajology More learning resources: https://pjreddie.com/darknet/yolo/ https://timebutt.github.io/static/how-to-train-yolov2-to-detect-custom-objects/ http://machinethink.net/blog/object-detection-with-yolo/ https://github.com/pjreddie/darknet/wiki/YOLO:-Real-Time-Object-Detection https://github.com/KleinYuan/easy-yolo https://medium.com/@xslittlegrass/almost-real-time-vehicle-detection-using-yolo-da0f016b43de https://medium.com/diaryofawannapreneur/yolo-you-only-look-once-for-object-detection-explained-6f80ea7aaa1e Join us in the Wizards Slack channel: http://wizards.herokuapp.com/ And please support me on Patreon: https://www.patreon.com/user?u=3191693 Instagram: https://www.instagram.com/sirajraval/ Signup for my newsletter for exciting updates in the field of AI: https://goo.gl/FZzJ5w
Views: 587647 Siraj Raval
C++Now 2018: Bob Steagall “Fast Conversion From UTF-8 with C++, DFAs, and SSE Intrinsics”
 
01:30:51
http://cppnow.org — Presentation Slides, PDFs, Source Code and other presenter materials are available at: http://cppnow.org/history/2018/talks/ — UTF-8 is taking on an increasingly important role in text processing. Many applications require the conversion of UTF-8 to UTF-16 or UTF-32, but typical conversion algorithms are sub-optimal. This talk will describe a fast, correct, DFA-based approach to UTF-8 conversion that requires only three simple lookup tables and a small amount of straightforward C++ code. We'll begin with a quick review UTF-8 and its relation to UTF-16 and UTF-32, as well as the concept of code units and code points. Next, we'll look at the layout of bits within a UTF-8 byte sequence, and from that, show a simple algorithm for converting from UTF-8 to UTF-32. Along the way will be a definition of overlong and invalid byte sequences. Following that will be a discussion of how to construct a DFA to perform the same operations as the simple algorithm. We'll then look at code for the DFA traversal underlying the basic conversion algorithm, and how to gain an additional performance boost by using SSE intrinsics. Finally, we'll compare the performance of this approach to several commonly-available implementations on Windows and Linux, and show how it's possible to do significantly faster conversions. — Bob Steagall KEWB Computing https://bobsteagall.com I've been working in C++ for the last 25 years. The majority of my career has been spent in medical imaging, where I led teams building applications for functional MRI and CT-based cardiac visualization. After a brief detour through the world of DNS and analytics, I'm now working in the area of distributed stream processing. — Videos Filmed & Edited by Bash Films: http://www.BashFilms.com
Views: 2572 BoostCon
How to Make a Calculator in C# Windows Form Application Part-1
 
20:35
Source code - http://www.codebind.com/c-sharp/make-calculator-c-windows-form-application/ -------------------Online Courses to learn---------------------------- Data Analytics with R Certification Training- http://bit.ly/2rSKHNP DevOps Certification Training - http://bit.ly/2T5P6bQ AWS Architect Certification Training - http://bit.ly/2PRHDeF Python Certification Training for Data Science - http://bit.ly/2BB3PV8 Java, J2EE & SOA Certification Training - http://bit.ly/2EKbwMK AI & Deep Learning with TensorFlow - http://bit.ly/2AeIHUR Big Data Hadoop Certification Training- http://bit.ly/2ReOl31 AWS Architect Certification Training - http://bit.ly/2EJhXjk Selenium Certification Training - http://bit.ly/2BFrfZs Tableau Training & Certification - http://bit.ly/2rODzSK Linux Administration Certification Training-http://bit.ly/2Gy9GQH ----------------------Follow--------------------------------------------- My Website - http://www.codebind.com My Blog - https://goo.gl/Nd2pFn My Facebook Page - https://goo.gl/eLp2cQ Google+ - https://goo.gl/lvC5FX Twitter - https://twitter.com/ProgrammingKnow Pinterest - https://goo.gl/kCInUp Text Case Converter - https://goo.gl/pVpcwL ------------------Facebook Links ---------------------------------------- http://fb.me/ProgrammingKnowledgeLearning/ http://fb.me/AndroidTutorialsForBeginners http://fb.me/Programmingknowledge http://fb.me/CppProgrammingLanguage http://fb.me/JavaTutorialsAndCode http://fb.me/SQLiteTutorial http://fb.me/UbuntuLinuxTutorials http://fb.me/EasyOnlineConverter Windows 8 Simple Calculator sample in C# for Visual Studio Visual Studio WinForm Windows Calculator Tutorial Sample Calculator with windows form application in c# Creating a Calculator Visual Studio C# Calculator in C# (Windows Application) how to create calculater in window application with c# A Calculator using C# Simple Calculator in C# Creating A Calculator Using Windows Form Application Make simple calculator in c# windows form application calculator code in c# windows form application calculator program in c# using windows forms window form application in c#
Views: 521860 ProgrammingKnowledge
Logistic Regression Machine Learning Method Using Scikit Learn and Pandas Python - Tutorial 31
 
13:28
In this Python for Data Science Tutorial, You will learn about how to do Logistic regression, a Machine learning method, using Scikit learn and Pandas scipy in python using Jupyter notebook. Checking for Independence in Logistic regression. Checking for Missing Values checking for target is ordinal or binary Deploying and Evaluating logistic model This is the 31th Video of Python for Data Science Course! In This series I will explain to you Python and Data Science all the time! It is a deep rooted fact, Python is the best programming language for data analysis because of its libraries for manipulating, storing, and gaining understanding from data. Watch this video to learn about the language that make Python the data science powerhouse. Jupyter Notebooks have become very popular in the last few years, and for good reason. They allow you to create and share documents that contain live code, equations, visualizations and markdown text. This can all be run from directly in the browser. It is an essential tool to learn if you are getting started in Data Science, but will also have tons of benefits outside of that field. Harvard Business Review named data scientist "the sexiest job of the 21st century." Python pandas is a commonly-used tool in the industry to easily and professionally clean, analyze, and visualize data of varying sizes and types. We'll learn how to use pandas, Scipy, Sci-kit learn and matplotlib tools to extract meaningful insights and recommendations from real-world datasets. Download Link for Cars Data Set: https://www.4shared.com/s/fWRwKoPDaei Download Link for Enrollment Forecast: https://www.4shared.com/s/fz7QqHUivca Download Link for Iris Data Set: https://www.4shared.com/s/f2LIihSMUei https://www.4shared.com/s/fpnGCDSl0ei Download Link for Snow Inventory: https://www.4shared.com/s/fjUlUogqqei Download Link for Super Store Sales: https://www.4shared.com/s/f58VakVuFca Download Link for States: https://www.4shared.com/s/fvepo3gOAei Download Link for Spam-base Data Base: https://www.4shared.com/s/fq6ImfShUca Download Link for Parsed Data: https://www.4shared.com/s/fFVxFjzm_ca Download Link for HTML File: https://www.4shared.com/s/ftPVgKp2Lca
Views: 24900 TheEngineeringWorld
C# - get youtube video data Part 2  [with source code]
 
10:54
C# get youtube video data Part 2, source code : http://1bestcsharp.blogspot.com/2014/10/c-create-simple-youtube-application.html All My Programming Projects Here --- http://bit.ly/2HrU8hK My Source Code Store --- http://bit.ly/2IhuXKA C# Course --- http://bit.ly/2rnt3C4 https://1bestcsharp.blogspot.com/ like us on https://www.facebook.com/1BestCsharp visit our blog https://1bestcsharp.blogspot.com/ Follow us on twitter: https://www.twitter.com/1BestCsharp_ *************************************************************************** *************************************************************************** C# And Java Programming Projects Source Code: http://1bestcsharp.blogspot.com/p/programming-projects.html *************************************************************************** *************************************************************************** in this apllication we will see -how to get source code from webpage (google chrome) in c# get the source code and disable it in richtextbox-how to play a youtube videos in c# get the link from textbox and change his form and put it in axshockwave (flash object)-how to get video title on richtextbox-how to get video description we will create 2 richtextbox one with the video description and the other for transfer the the date from the other-how to get video tags we will create 2 richtextbox one with the video tags and the other for transfer the the date from the other-how to get video thumbnail on picturebox get the picture link and save it into your pc-how to get video views count on label-how to get video like count on label-how to get video dislike count on label-how to get video published date on labeli hope that you like this app build with c# in visual studio 2010
Views: 1967 1BestCsharp blog
UML Class Diagram Tutorial
 
10:17
Learn how to make classes, attributes, and methods in this UML Class Diagram tutorial. There's also in-depth training and examples on inheritance, aggregation, and composition relationships. UML (or Unified Modeling Language) is a software engineering language that was developed to create a standard way of visualizing the design of a system. And UML Class Diagrams describe the structure of a system by showing the system’s classes and how they relate to one another. This tutorial explains several characteristics of class diagrams. Within a class, there are attributes, methods, visibility, and data types. All of these components help identify a class and explain what it does. There are also several different types of relationships that exist within UML Class Diagrams. Inheritance is when a child class (or subclass) takes on all the attributes and methods of the parent class (or superclass). Association is a very basic relationship where there's no dependency. Aggregation is a relationship where the part can exist outside the whole. And finally, Composition is when a part cannot exist outside the whole. A class would be destroyed if the class it's related to is destroyed. Further UML Class Diagram information: https://www.lucidchart.com/pages/uml-class-diagram —— Learn more and sign up: http://www.lucidchart.com Follow us: Facebook: https://www.facebook.com/lucidchart Twitter: https://twitter.com/lucidchart Instagram: https://www.instagram.com/lucidchart LinkedIn: https://www.linkedin.com/company/lucidsoftware —— Credits for Photos with Attribution Requirements Tortoise - by Niccie King - http://bit.ly/2uHaL1G Otter - by Michael Malz - http://bit.ly/2vrVoYt Slow Loris - by David Haring - http://bit.ly/2uiBWxg Creep - by Poorna Kedar - http://bit.ly/2twR4K8 Visitor Center - by McGheiver - http://bit.ly/2uip0Hq Lobby - by cursedthing - http://bit.ly/2twBWw9
Views: 752322 Lucidchart
Intro to Machine Learning with R & caret
 
01:42:33
Lecture starts at 3:00 The R programming language is experiencing rapid increases in popularity and wide adoption across industries. This popularity is due, in part, to R’s huge collection of open source machine learning algorithms. If you are a data scientist working with R, the caret package (short for [C]lassification [A]nd [RE]gression [T]raining) is a must-have tool in your toolbelt. The caret package provides capabilities that are ubiquitous in all stages of the data science project lifecycle. Most important of all, caret provides a common interface for training, tuning, and evaluating more than 200 machine learning algorithms. Not surprisingly, caret is a sure fire way to accelerate your velocity as a data scientist! In this presentation Dave Langer will provide an introduction to the caret package. The focus of the presentation will be using caret to implement some of the most common tasks of the data science project lifecycle and to illustrate incorporating caret into your daily work. Attendees will learn how to: • Create stratified random samples of data useful for training machine learning models. • Train machine learning models using caret’s common interface. • Leverage caret’s powerful features for cross-validation and hyperparameter tuning. • Scale caret via use of multi-core, parallel training. • Increase their knowledge of caret’s many features. R code and accompanying dataset: https://code.datasciencedojo.com/datasciencedojo/tutorials/tree/master/Introduction%20to%20Machine%20Learning%20with%20R%20and%20Caret caret website: http://topepo.github.io/caret/index.html Learn more about David here: https://www.meetup.com/data-science-dojo/events/239730653/ -- At Data Science Dojo, we believe data science is for everyone. Our in-person data science training has been attended by more than 3600+ from over 742 companies globally. This channel contains tutorials, community talks, and courses on data science and data engineering. -- Learn more about Data Science Dojo here: https://hubs.ly/H0f8wHn0 See what our past attendees are saying here: https://hubs.ly/H0f8wtJ0 -- Like Us: https://www.facebook.com/datasciencedojo/ Follow Us: https://twitter.com/DataScienceDojo Connect with Us: https://www.linkedin.com/company/data-science-dojo Also find us on: Google +: https://plus.google.com/+Datasciencedojo Instagram: https://www.instagram.com/data_science_dojo/ Vimeo: https://vimeo.com/datasciencedojo
Views: 40204 Data Science Dojo
Learn Objective C Tutorial For Beginners - Episode 5 - Memory Management
 
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Get a customized roadmap for your app and start building it in 7 days: ⚡ http://codewithchris.com/actionplan Learn Objective C Tutorial For Beginners is a series that introduces the Objective C programming language and teaches you how to write code to build iPhone apps. Learning Objective C doesn't have to be hard! In these tutorials, you will learn Objective C programming syntax, classes and software design patterns so that you can program iOS apps. Combined with the Learn XCode 4 Tutorial series, you'll be making iPhone apps in no time! In this episode, we talk about how Objective-C handles memory management! Source Code for this video: http://codewithchris.com/source-code/ For the all the episodes in this Learn Objective C Tutorial For Beginners series, visit the playlist: http://www.youtube.com/playlist?list=PLMRqhzcHGw1YfS92iytSJCjt01FxPF9rr For more XCode and Objective C Tutorials, visit my channel: http://www.youtube.com/user/CodeWithChris WEBSITE: http://codewithchris.com TWITTER: https://twitter.com/chriswching My channel, CodeWIthChris, is about all the aspects of building iOS apps. I'll post video tutorials on Objective C, XCode, how to submit apps to the Apple App Store, and tutorials on building various types of apps or integrating things like analytics, advertisements etc. You might even find the odd app review here or there! If you want to see more ObjectiveC and XCode Video Tutorials, please SUBSCRIBE so that you don't miss an episode and remember to LIKE and COMMENT if you have questions. Intro & Outro music "deche ok" by Gablé (http://www.gableboulga.com/)
Views: 10953 CodeWithChris
4 Tips for Computer Programming Beginners – Software Developer Guide
 
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Enroll for exercises, tutorials, courses, and projects... http://cleverprogrammer.io/enroll Let's talk about the top 4 best tips you must learn to excel in the software developer world! Use these as a guide to learn any computer programming language like c++, javascript, python, and much more! Start your coding career right using these tips. Enroll in Learn Python™ OOP (Create Apps) course: http://cleverprogrammer.io/enroll ================================================== Connect With Me! Website ► http://cleverprogrammer.io/enroll Facebook ► http://cleverprogrammer.io/facebook Twitter ► http://cleverprogrammer.io/twitter Instagram ► http://cleverprogrammer.io/instagram Snapchat ► Rafeh1 iTunes Podcast ► http://cleverprogrammer.io/podcast Google Podcast ► http://cleverprogrammer.io/google-podcast Support (Patreon) ► http://cleverprogrammer.io/patreon Youtube ► https://www.youtube.com/c/CleverProgrammer Fake Love Credits – AriGoldMusic
Views: 254637 Clever Programmer
IS DISCORD REALLY THE BEST? - Voice Chat Platform Showdown
 
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The voice chat scene has long been dominated by TeamSpeak, Mumble, and Skype. Discord aims to change that, but is it really up to snuff? Freshbooks sponsor link: For your unrestricted 30 days free trial, go to https://www.freshbooks.com/techtips and enter in “Linus Tech Tips” in the how you heard about us section. bequiet sponsor link: Check out bequiet's white Dark Base Pro 900: http://geni.us/ltfG0ve Buy Microphones Amazon: http://geni.us/0Pqgh Newegg: http://geni.us/N16HC Discuss on the forum: https://linustechtips.com/main/topic/853977-is-discord-really-the-best-voice-chat-platform-showdown/ Download the recordings here: http://geni.us/wOMLuW Our Affiliates, Referral Programs, and Sponsors: https://linustechtips.com/main/topic/75969-linus-tech-tips-affiliates-referral-programs-and-sponsors Linus Tech Tips merchandise at http://www.designbyhumans.com/shop/LinusTechTips/ Linus Tech Tips posters at http://crowdmade.com/linustechtips Our production gear: http://geni.us/cvOS Twitter - https://twitter.com/linustech Facebook - http://www.facebook.com/LinusTech Instagram - https://www.instagram.com/linustech Twitch - https://www.twitch.tv/linustech Intro Screen Music Credit: Title: Laszlo - Supernova Video Link: https://www.youtube.com/watch?v=PKfxmFU3lWY iTunes Download Link: https://itunes.apple.com/us/album/supernova/id936805712 Artist Link: https://soundcloud.com/laszlomusic Outro Screen Music Credit: Approaching Nirvana - Sugar High http://www.youtube.com/approachingnirvana Sound effects provided by http://www.freesfx.co.uk/sfx/
Views: 2209954 Linus Tech Tips
Import Data, Copy Data from Excel to R CSV & TXT Files | R Tutorial 1.5 |MarinStatsLectures
 
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Import Data, Copy Data from Excel (or other spreadsheets) to R CSV & TXT Files; Practice with Dataset: (https://bit.ly/2rOfgEJ) More Statistics and R Programming Tutorials: https://bit.ly/2Fhu9XU How to Import CSV data into R or How to Import TXT files into R from Excel or other spreadsheets using function in R ►How to import CSV data into R? We will be using "read.table" function to import comma separated data into R ► How to import txt data file into R? You will learn to use "read.delim" function to import the tab-delimited text file into R ► You will also learn to use "file.choose" argument for file location, "header" argument to let R know the data has headers or variable names and "sep" argument to let R know how the data values are separated. ►►Download the dataset here: https://statslectures.com/r-scripts-datasets ►►Like to support us? You can Donate https://bit.ly/2CWxnP2 or Share the Videos! ►► Watch More: ► Intro to Statistics Course: https://bit.ly/2SQOxDH ►R Tutorials for Data Science https://bit.ly/1A1Pixc ►Getting Started with R (Series 1): https://bit.ly/2PkTneg ►Graphs and Descriptive Statistics in R (Series 2): https://bit.ly/2PkTneg ►Probability distributions in R (Series 3): https://bit.ly/2AT3wpI ►Bivariate analysis in R (Series 4): https://bit.ly/2SXvcRi ►Linear Regression in R (Series 5): https://bit.ly/1iytAtm ►ANOVA series https://bit.ly/2zBwjgL ►Linear Regression Concept and with R https://bit.ly/2z8fXg1 ►Puppet Master of Statistics: https://bit.ly/2RDAAv4 ►Hypothesis Testing: Concepts in Statistics https://bit.ly/2Ff3J9e ◼︎ Table of Content 0:00:17 What are the two main file types for saving a data file (CSV and TXT) 0:00:36 How to save an Excel file as a CSV file (comma-separated value) 0:01:10 How to open a CSV data file in Excel 0:01:20 How to open a CSV file in a text editor 0:01:36 How to import CSV file into R? using read.csv function 0:01:44 How to access the help menu for different commands/functions in R 0:02:04 How to specify file location for R? using file.choose argument on read.csv function 0:02:31 How to let R know our data has headers or variable names when importing the data into R? By using the “header” argument on read.csv function 0:03:22 How to import CSV file into R? using read.table function 0:03:38 How to specify the file location for the read.table function in R? using file.choose argument 0:03:46 How to specify how variables/columns are separated when importing data into R? the "sep" argument on read.table function will do that; for example if you don't specify that your data is comma separated, R ends up reading it all in as one variable 0:04:10 How to save a file in Excel as tab-delimited text (TXT) file 0:04:50 How to open a tab-delimited (.TXT) data file in a text editor 0:05:07 How to open a tab-delimited (.TXT) data file in excel 0:05:20 How to import tab-delimited (.TXT) data file into R? using read.delim function 0:05:44 How to specify the file path for read.delim function in R? using file.choose argument 0:06:06 How to import tab-delimited (.TXT) data file into R? using read.table function 0:06:23 How to specify that the data has headers or variable names when importing the data into R? using header argument on read.table function This video is a tutorial for programming in R Statistical Software for beginners, using RStudio. Follow MarinStatsLectures Subscribe: https://goo.gl/4vDQzT website: https://statslectures.com Facebook:https://goo.gl/qYQavS Twitter:https://goo.gl/393AQG Instagram: https://goo.gl/fdPiDn Our Team: Content Creator: Mike Marin (B.Sc., MSc.) Senior Instructor at UBC. Producer and Creative Manager: Ladan Hamadani (B.Sc., BA., MPH) These videos are created by #marinstatslectures to support some courses at The University of British Columbia (UBC) (#IntroductoryStatistics and #RVideoTutorials for Health Science Research), although we make all videos available to the everyone everywhere for free. Thanks for watching! Have fun and remember that statistics is almost as beautiful as a unicorn!
Programming 7: Using Twitter API in Processing
 
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Video for introduction to real-time interactive graphical programming, using the free Processing development environment. This reflects information covered in the lab sessions for LMC 6310, Computing as an Expressive Medium, a course in the Digital Media master's program at Georgia Tech.
Views: 5617 GATechDM Courses
Python: How to open Big Data Files Buffering Tutorial
 
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This tutorial video covers how to open big data files in Python using buffering. The idea here is to efficiently open files, or even to open files that are too large to be read into memory.
Views: 17919 sentdex
Haar Cascade Object Detection Face & Eye - OpenCV with Python for Image and Video Analysis 16
 
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In this OpenCV with Python tutorial, we're going to discuss object detection with Haar Cascades. We'll do face and eye detection to start. In order to do object recognition/detection with cascade files, you first need cascade files. For the extremely popular tasks, these already exist. Detecting things like faces, cars, smiles, eyes, and license plates for example are all pretty prevalent. First, I will show you how to use these cascade files, then I will show you how to embark on creating your very own cascades, so that you can detect any object you want, which is pretty darn cool! You can use Google to find various Haar Cascades of things you may want to detect. You shouldn't have too much trouble finding the aforementioned types. We will use a Face cascade and Eye cascade. You can find a few more at the root directory of Haar cascades. Note the license for using/distributing these Haar Cascades. text-based tutorial and sample code: https://pythonprogramming.net/haar-cascade-face-eye-detection-python-opencv-tutorial/ https://pythonprogramming.net https://twitter.com/sentdex https://www.facebook.com/pythonprogramming.net/ https://plus.google.com/+sentdex
Views: 395236 sentdex
RTC 3.0:  Context-Aware Search for source code using semantic analysis of related artifacts
 
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Determining where functionality is implemented or what existing code may be relevant for understanding and implementing a work item can be difficult using conventional search technologies. A developer may need to already be highly familiar with existing details such as code organization and naming conventions to be able to use regular expression and other wild-card style searches effectively. In large projects such searches may not be practical, and the developer instead relies on acquired insight. Context-Aware Search enables searching using natural language rather than exact patterns. This capability allows analysis of a work item for relevant keywords. Using these keywords it then locates source code that may be relevant for the work item.
Views: 1590 Jazz.net