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Natural Language Processing (NLP) & Text Mining Tutorial Using NLTK | NLP Training | Edureka
 
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** NLP Using Python: - https://www.edureka.co/python-natural-language-processing-course ** This Edureka video will provide you with a comprehensive and detailed knowledge of Natural Language Processing, popularly known as NLP. You will also learn about the different steps involved in processing the human language like Tokenization, Stemming, Lemmatization and much more along with a demo on each one of the topics. The following topics covered in this video : 1. The Evolution of Human Language 2. What is Text Mining? 3. What is Natural Language Processing? 4. Applications of NLP 5. NLP Components and Demo Do subscribe to our channel and hit the bell icon to never miss an update from us in the future: https://goo.gl/6ohpTV --------------------------------------------------------------------------------------------------------- Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka Instagram: https://www.instagram.com/edureka_learning/ --------------------------------------------------------------------------------------------------------- - - - - - - - - - - - - - - How it Works? 1. This is 21 hrs of Online Live Instructor-led course. Weekend class: 7 sessions of 3 hours each. 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. At the end of the training you will have to undergo a 2-hour LIVE Practical Exam based on which we will provide you a Grade and a Verifiable Certificate! - - - - - - - - - - - - - - About the Course Edureka's Natural Language Processing using Python Training focuses on step by step guide to NLP and Text Analytics with extensive hands-on using Python Programming Language. It has been packed up with a lot of real-life examples, where you can apply the learnt content to use. Features such as Semantic Analysis, Text Processing, Sentiment Analytics and Machine Learning have been discussed. This course is for anyone who works with data and text– with good analytical background and little exposure to Python Programming Language. It is designed to help you understand the important concepts and techniques used in Natural Language Processing using Python Programming Language. You will be able to build your own machine learning model for text classification. Towards the end of the course, we will be discussing various practical use cases of NLP in python programming language to enhance your learning experience. -------------------------- Who Should go for this course ? Edureka’s NLP Training is a good fit for the below professionals: From a college student having exposure to programming to a technical architect/lead in an organisation Developers aspiring to be a ‘Data Scientist' Analytics Managers who are leading a team of analysts Business Analysts who want to understand Text Mining Techniques 'Python' professionals who want to design automatic predictive models on text data "This is apt for everyone” --------------------------------- Why Learn Natural Language Processing or NLP? Natural Language Processing (or Text Analytics/Text Mining) applies analytic tools to learn from collections of text data, like social media, books, newspapers, emails, etc. The goal can be considered to be similar to humans learning by reading such material. However, using automated algorithms we can learn from massive amounts of text, very much more than a human can. It is bringing a new revolution by giving rise to chatbots and virtual assistants to help one system address queries of millions of users. NLP is a branch of artificial intelligence that has many important implications on the ways that computers and humans interact. Human language, developed over thousands and thousands of years, has become a nuanced form of communication that carries a wealth of information that often transcends the words alone. NLP will become an important technology in bridging the gap between human communication and digital data. --------------------------------- For more information, please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll-free).
Views: 35890 edureka!
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 Hit the Join button above to sign up to become a member of my channel for access to exclusive content!
Views: 100463 Siraj Raval
Natural Language Processing in Python
 
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Alice Zhao https://pyohio.org/2018/schedule/presentation/38/ Natural language processing (NLP) is an exciting branch of artificial intelligence (AI) that allows machines to break down and understand human language. As a data scientist, I often use NLP techniques to interpret text data that I'm working with for my analysis. During this tutorial, I plan to walk through text pre-processing techniques, machine learning techniques and Python libraries for NLP. Text pre-processing techniques include tokenization, text normalization and data cleaning. Once in a standard format, various machine learning techniques can be applied to better understand the data. This includes using popular modeling techniques to classify emails as spam or not, or to score the sentiment of a tweet on Twitter. Newer, more complex techniques can also be used such as topic modeling, word embeddings or text generation with deep learning. We will walk through an example in Jupyter Notebook that goes through all of the steps of a text analysis project, using several NLP libraries in Python including NLTK, TextBlob, spaCy and gensim along with the standard machine learning libraries including pandas and scikit-learn. ## Setup Instructions [ https://github.com/adashofdata/nlp-in-python-tutorial](https://github.com/adashofdata/nlp-in-python-tutorial) === https://pyohio.org A FREE annual conference for anyone interested in Python in and around Ohio, the entire Midwest, maybe even the whole world.
Views: 17941 PyOhio
StanfordCoreNLP Demo 1
 
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Final Project Presentation for Natural Language Processing - Spring 2017
Views: 5444 aikmanrules
Weka Text Classification for First Time & Beginner Users
 
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59-minute beginner-friendly tutorial on text classification in WEKA; all text changes to numbers and categories after 1-2, so 3-5 relate to many other data analysis (not specifically text classification) using WEKA. 5 main sections: 0:00 Introduction (5 minutes) 5:06 TextToDirectoryLoader (3 minutes) 8:12 StringToWordVector (19 minutes) 27:37 AttributeSelect (10 minutes) 37:37 Cost Sensitivity and Class Imbalance (8 minutes) 45:45 Classifiers (14 minutes) 59:07 Conclusion (20 seconds) Some notable sub-sections: - Section 1 - 5:49 TextDirectoryLoader Command (1 minute) - Section 2 - 6:44 ARFF File Syntax (1 minute 30 seconds) 8:10 Vectorizing Documents (2 minutes) 10:15 WordsToKeep setting/Word Presence (1 minute 10 seconds) 11:26 OutputWordCount setting/Word Frequency (25 seconds) 11:51 DoNotOperateOnAPerClassBasis setting (40 seconds) 12:34 IDFTransform and TFTransform settings/TF-IDF score (1 minute 30 seconds) 14:09 NormalizeDocLength setting (1 minute 17 seconds) 15:46 Stemmer setting/Lemmatization (1 minute 10 seconds) 16:56 Stopwords setting/Custom Stopwords File (1 minute 54 seconds) 18:50 Tokenizer setting/NGram Tokenizer/Bigrams/Trigrams/Alphabetical Tokenizer (2 minutes 35 seconds) 21:25 MinTermFreq setting (20 seconds) 21:45 PeriodicPruning setting (40 seconds) 22:25 AttributeNamePrefix setting (16 seconds) 22:42 LowerCaseTokens setting (1 minute 2 seconds) 23:45 AttributeIndices setting (2 minutes 4 seconds) - Section 3 - 28:07 AttributeSelect for reducing dataset to improve classifier performance/InfoGainEval evaluator/Ranker search (7 minutes) - Section 4 - 38:32 CostSensitiveClassifer/Adding cost effectiveness to base classifier (2 minutes 20 seconds) 42:17 Resample filter/Example of undersampling majority class (1 minute 10 seconds) 43:27 SMOTE filter/Example of oversampling the minority class (1 minute) - Section 5 - 45:34 Training vs. Testing Datasets (1 minute 32 seconds) 47:07 Naive Bayes Classifier (1 minute 57 seconds) 49:04 Multinomial Naive Bayes Classifier (10 seconds) 49:33 K Nearest Neighbor Classifier (1 minute 34 seconds) 51:17 J48 (Decision Tree) Classifier (2 minutes 32 seconds) 53:50 Random Forest Classifier (1 minute 39 seconds) 55:55 SMO (Support Vector Machine) Classifier (1 minute 38 seconds) 57:35 Supervised vs Semi-Supervised vs Unsupervised Learning/Clustering (1 minute 20 seconds) Classifiers introduces you to six (but not all) of WEKA's popular classifiers for text mining; 1) Naive Bayes, 2) Multinomial Naive Bayes, 3) K Nearest Neighbor, 4) J48, 5) Random Forest and 6) SMO. Each StringToWordVector setting is shown, e.g. tokenizer, outputWordCounts, normalizeDocLength, TF-IDF, stopwords, stemmer, etc. These are ways of representing documents as document vectors. Automatically converting 2,000 text files (plain text documents) into an ARFF file with TextDirectoryLoader is shown. Additionally shown is AttributeSelect which is a way of improving classifier performance by reducing the dataset. Cost-Sensitive Classifier is shown which is a way of assigning weights to different types of guesses. Resample and SMOTE are shown as ways of undersampling the majority class and oversampling the majority class. Introductory tips are shared throughout, e.g. distinguishing supervised learning (which is most of data mining) from semi-supervised and unsupervised learning, making identically-formatted training and testing datasets, how to easily subset outliers with the Visualize tab and more... ---------- Update March 24, 2014: Some people asked where to download the movie review data. It is named Polarity_Dataset_v2.0 and shared on Bo Pang's Cornell Ph.D. student page http://www.cs.cornell.edu/People/pabo/movie-review-data/ (Bo Pang is now a Senior Research Scientist at Google)
Views: 136812 Brandon Weinberg
Getting Started with Natural Language Processing in Java : Simple Java Tokenizers | packtpub.com
 
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This playlist/video has been uploaded for Marketing purposes and contains only selective videos. For the entire video course and code, visit [http://bit.ly/2xhnAS7]. The aim of this video is to demonstrate core Java tokenizers. • Learn to use the Scanner class to tokenize text • Learn how to use the BreakIterator class for tokenization • Learn how to use the StringTokenizer For the latest Big Data and Business Intelligence video tutorials, please visit http://bit.ly/1HCjJik Find us on Facebook -- http://www.facebook.com/Packtvideo Follow us on Twitter - http://www.twitter.com/packtvideo
Views: 6495 Packt Video
Weka Data Mining Tutorial for First Time & Beginner Users
 
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23-minute beginner-friendly introduction to data mining with WEKA. Examples of algorithms to get you started with WEKA: logistic regression, decision tree, neural network and support vector machine. Update 7/20/2018: I put data files in .ARFF here http://pastebin.com/Ea55rc3j and in .CSV here http://pastebin.com/4sG90tTu Sorry uploading the data file took so long...it was on an old laptop.
Views: 457183 Brandon Weinberg
Lingpipe Tutorial for beginners - Introduction & Documentation
 
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LingPipe is tool kit for processing text using computational linguistics. Here's a brief tutorial on getting started with it.. I'm using Eclipse Oxygen with Lingpipe 4.0.1
Views: 470 Everything Q
Mallet Presentation
 
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Mallet Presentation COT6930 Natural Language Processing Spring 2017
Views: 544 Angel San
5 Tools for Every Software Developer
 
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1. Editors Atom : https://atom.io/ Atom is a text editor that's modern, approachable, yet hackable to the core—a tool you can customize to do anything but also use productively without ever touching a config file. Sublime : https://www.sublimetext.com/ A sophisticated text editor for code, markup and prose Eclipse : https://www.eclipse.org/ Eclipse is an IDE used in computer programming, and is the most widely used Java IDE. Visual Studio : https://www.visualstudio.com/ Microsoft Visual Studio is an IDE from Microsoft to develop computer programs for Microsoft Windows, web sites, web apps, web services and mobile apps. Netbeans : https://netbeans.org/ Quickly and easily develop desktop, mobile and web applications with Java, JavaScript, HTML5, PHP, C/C++ and more. IntelliJ : https://www.jetbrains.com/idea/ IntelliJ IDEA is a Java integrated development environment for developing computer software. 2. Code Sharing Platforms git : https://git-scm.com/ Git is easy to learn and has a lightning fast performance. It outclasses SCM tools like Subversion, CVS, Perforce, and ClearCase with its features. GitHub : https://github.com/ With it you can host and review code, manage projects, and build software alongside millions of other developers. Bitbucket : https://bitbucket.org/ Distributed version control system that makes it easy for you to collaborate with your team. GitLab : https://about.gitlab.com/ Create value faster with a single application for the whole software development and operations lifecycle. 4 Communication platform Slack : https://slack.com/ Slack is the platform that connects teams with the apps, services, and resources they need to get work done. 5. Continuous Integration Jenkins : https://jenkins.io/ The leading open source automation server, Jenkins provides hundreds of plugins to support building, deploying and automating any project. This video does not explain how to use the tools but top 5 tools available which you should use. You don't need to learn new programming languages to make your softaware building process better. Instead you can learn new tools to increase the productivity. In this video we will see 5 such tools 1. Editor You need a good editor (can be editor or IDE). eg Atom, sublime, eclipse, visual studio, netbeans 2. Code Sharing Platform Git, GitHub, BitBucket, GitLab 3. Linux Shell Programming, Command prompt(both windows and linux base). A shell script is a computer program designed to be run by the Unix shell, a command-line interpreter. The various dialects of shell scripts are considered to be scripting languages. 4. Communication platform There are many service providers in markets for communication most famous now a days are emails and whatsapp. Slack 5. Continuous integration Jenkins some more tools : 6. Browser apps eg firebug, postman 7. Cloud services Editing Monitors : https://amzn.to/2RfKWgL https://amzn.to/2Q665JW https://amzn.to/2OUP21a. Check out our website: http://www.telusko.com Follow Telusko on Twitter: https://twitter.com/navinreddy20 Follow on Facebook: Telusko : https://www.facebook.com/teluskolearn... Navin Reddy : https://www.facebook.com/navintelusko Follow Navin Reddy on Instagram: https://www.instagram.com/navinreddy20 Subscribe to our other channel: Navin Reddy : https://www.youtube.com/channel/UCxmk... Telusko Hindi : https://www.youtube.com/channel/UCitz... Donation: PayPal Id : navinreddy20 Patreon : navinreddy20 http://www.telusko.com/contactus
Views: 95113 Telusko
NLP : Auto correction with Text in Python
 
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The application of computational techniques to the analysis and synthesis of natural language and speech. Python Core ------------ Video in English https://goo.gl/df7GXL Video in Tamil https://goo.gl/LT4zEw Python Web application ---------------------- Videos in Tamil https://goo.gl/rRjs59 Videos in English https://goo.gl/spkvfv Python NLP ----------- Videos in Tamil https://goo.gl/LL4ija Videos in English https://goo.gl/TsMVfT Artificial intelligence and ML ------------------------------ Videos in Tamil https://goo.gl/VNcxUW Videos in English https://goo.gl/EiUB4P ChatBot -------- Videos in Tamil https://goo.gl/JU2WPk Videos in English https://goo.gl/KUZ7PY YouTube channel link www.youtube.com/atozknowledgevideos Website http://atozknowledge.com/ Technology in Tamil & English
Views: 2772 atoz knowledge
Mallet Quick Start Tutorial
 
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Mallet Project COT6930 Natural Language Processing Spring 2017
Views: 2112 Angel San
Speech Recognition using Python
 
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Speech Recognition using Python Learn how to convert audio into text using python. Code here : https://github.com/umangahuja1/Youtube/blob/master/Python_Extras/speech.py Stay Tuned :) Follow here for more Quora : https://getsetpython.quora.com/ Facebook : https://www.facebook.com/getsetpython/ Twitter : https://twitter.com/umangahuja_1
Views: 78126 Get Set Python
Module 1: Introduction to GATE Developer
 
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This module will introduce you to the GATE Developer interface. It explains the different viewing panes, resources and the various options you can set within GATE Developer.
Views: 4952 Rilfi Mohamed
Getting Started with Weka - Machine Learning Recipes #10
 
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Hey everyone! In this video, I’ll walk you through using Weka - The very first machine learning library I’ve ever tried. What’s great is that Weka comes with a GUI that makes it easy to visualize your datasets, and train and evaluate different classifiers. I’ll give you a quick walkthrough of the tool, from installation all the way to running experiments, and show you some of what it can do. This is a helpful library to have while you’re learning ML, and I still find it useful today to experiment with new datasets. Note: In the video, I quickly went through testing. This is an important topic in ML, and how you design and evaluate your experiments is even more important than the classifier you use. Although I publish these videos at turtle speed, I’ve started working on an experimental design one, and that’ll be next! Also, we will soon publish some testing tips and best practices on tensorflow.org (https://goo.gl/nZcS5R). Links from the video: Weka → https://goo.gl/2TYjGZ Ready to use datasets → https://goo.gl/PM8DtH More on evaluating classifiers, particularly in the medical domain → https://goo.gl/TwTYyk Check out the Machine Learning Recipes playlist → https://goo.gl/KewA03 Follow Josh on Twitter → https://twitter.com/random_forests Subscribe to the Google Developers channel → http://goo.gl/mQyv5L
Views: 69626 Google Developers
Natural Language Processing (NLP) Tutorial with Python & NLTK
 
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This video will provide you with a comprehensive and detailed knowledge of Natural Language Processing, popularly known as NLP. You will also learn about the different steps involved in processing the human language like Tokenization, Stemming, Lemmatization and more. Python, NLTK, & Jupyter Notebook are used to demonstrate the concepts. This tutorial was developed by Edureka. 🔗NLP Certification Training: https://goo.gl/kn2H8T 🔗Subscribe to the Edureka YouTube channel: https://www.youtube.com/user/edurekaIN 🔗Edureka Online Training: https://www.edureka.co/ -- Learn to code for free and get a developer job: https://www.freecodecamp.org Read hundreds of articles on programming: https://medium.freecodecamp.org And subscribe for new videos on technology every day: https://youtube.com/subscription_center?add_user=freecodecamp
Views: 14475 freeCodeCamp.org
How to install Java JDK on Mac OS X ( with JAVA_HOME )
 
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How to install Java JDK Java Development Kit on mac. In Mac OSX 10.5 or later, Apple recommends to set the $JAVA_HOME variable to /usr/libexec/java_home, just export $JAVA_HOME in file ~/. bash_profile or ~/.profile. $ vim .bash_profile export JAVA_HOME=$(/usr/libexec/java_home) $ echo $JAVA_HOME /Library/Java/JavaVirtualMachines/1.7.0.jdk/Contents/Home JRE Installation for Mac OS X (64-bit). How to Set $JAVA_HOME environment variable on Mac OS X -------------------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: 271656 ProgrammingKnowledge
IBM Watson: Java-SDK tutorial
 
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Write a locally running Java program that uses IBM Watson services.
Views: 9006 Asher Stern
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: 102324 sentdex
Java for z/OS APIS
 
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Audience: Java Developers Can do what: Easily write and deploy Java applications that make use of services that are unique to z/OS. Why is it important: Java for z/OS provides a set of helper classes called the JZOS toolkit. This API toolkit helps Java developers make use of unique mainframe services right inside their Java applications. services like: accessing traditional mainframe datasets, submitting jobs, communicating with system consoles, interop with COBOL or Assembler transaction data.
Views: 1286 zDeveloper Community
Content extraction with Apache Tika
 
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Presentation slides available here: http://www.lucenerevolution.org/past_events Apache Tika is a toolkit for detecting and extracting metadata and structured text content from various documents using existing parser libraries. To show how the toolkit can be used with a Lucene or Solr search index, this talk covers Introduction to Apache Tika Full text extraction with Tika Using the Tika-based ExtractingRequestHandler in Solr Integrating Tika directly with Lucene Link extraction for web crawlers Advanced features like forked parsing and the Tika server This talk assumes basic knowledge of Lucene or Solr and of Java programming.
Views: 26551 LuceneSolrRevolution
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: 164853 Timothy DAuria
EmoText for opinion mining in long texts
 
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http://socioware.de https://www.researchgate.net/publication/278383087_Opinion_Mining_and_Lexical_Affect_Sensing EmoText for opinion mining in long texts illustrates a domain-independent approach to opinion mining. A thorough description is available in the book "Opinion mining and lexical affect sensing". Empirically revealed that texts should contain not less than 200 words for reliable classification. The engine evaluates features (lexical, stylometric, grammatical, deictic) using different evaluation methods and uses the SMO or NaiveBayes classifiers from the WEKA data mining toolkit for text classification. Statistical EmoText formed a basis for the statistical framework for experimentation and rapid prototyping. The approach was tested on the following English corpora: a Pang corpus with weblogs, Berardinelli movie review corpus with movie reviews, a corpus with spontaneous dialogues (the SAL corpus), and a corpus with product reviews.
Views: 972 Alexander Osherenko
Text Mining and Analytics Made Easy with DSTK Text Explorer
 
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DSTK - Data Science Toolkit offers Data Science softwares to help users in data mining and text mining tasks. DSTK follows closely to CRISP DM model. DSTK offers data understanding using statistical and text analysis, data preparation using normalization and text processing, modeling and evaluation for machine learning and statistical learning algorithms. DSTK Text Explorer helps user to do text mining and text analytics task easily. It allows text processing using stopwords, stemming, uppercase, lowercase and etc. It also has features in sentiment analysis, text link analysis, name entity, pos tagging, text classification using stanford nlp classifier. It allows data scraping from images, videos, and webscraping from websites. For more information, visit: http://dstk.tech
Views: 3639 SVBook
Installing Java WindowBuilder (Gui Designer Plugin ) on Eclipse
 
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In this video I am going to show How to install Java WindowBuilder (Gui Designer Plugin ) on Eclipse IDE. This method we can you to install Java WindowBuilder plugin on Windows 10, Windows 8, Ubuntu, Mac Os or any other Linux operating system. -------------------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 eclipse java windowbuilder tutorial windowbuilder eclipse indigo install window builder eclipse java gui builder eclipse plugin java gui designer eclipse plugin Visual Swing for Eclipse java swing plugin for eclipse Installing WindowBuilder Pro - Eclipse Installation Instructions java eclipse windowbuilder
Views: 548367 ProgrammingKnowledge
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 Hit the Join button above to sign up to become a member of my channel for access to exclusive content!
Views: 195432 Siraj Raval
YOLO Object Detection (TensorFlow tutorial)
 
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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 Hit the Join button above to sign up to become a member of my channel for access to exclusive content!
Views: 640311 Siraj Raval
Automatic Time Table Generation Using Genetic Algorithm
 
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Title: Automatic Time Table Generation Using Genetic Algorithm Domain: Data Mining Key Features: 1. Generation of time table using genetic algorithm. 2. Time table generation separately for teacher and students. 3. Downloadable in .xls file 4. Facility of curd model for teacher and students, etc. For more details contact: E-Mail: [email protected] Buy Whole Project Kit for Rs 5000%. Project Kit: • 1 Review PPT • 2nd Review PPT • Full Coding with described algorithm • Video File • Full Document Note: *For bull purchase of projects and for outsourcing in various domains such as Java, .Net, .PHP, NS2, Matlab, Android, Embedded, Bio-Medical, Electrical, Robotic etc. contact us. *Contact for Real Time Projects, Web Development and Web Hosting services. *Comment and share on this video and win exciting developed projects for free of cost. Search Terms: 1. 2017 ieee projects 2. latest ieee projects in java 3. latest ieee projects in data mining 4. 2016 – 2017 data mining projects 5. 2016 – 2017 best project center in Chennai 6. best guided ieee project center in Chennai 7. 2016 – 2017 ieee titles 8. 2016 – 2017 base paper 9. 2016 – 2017 java projects in Chennai, Coimbatore, Bangalore, and Mysore 10. time table generation projects 11. instruction detection projects in data mining, network security 12. 2016 – 2017 data mining weka projects 13. 2016 – 2017 b.e projects 14. 2016 – 2017 m.e projects 15. 2016 – 2017 final year projects 16. affordable final year projects 17. latest final year projects 18. best project center in Chennai, Coimbatore, Bangalore, and Mysore 19. 2017 Best ieee project titles 20. best projects in java domain 21. free ieee project in Chennai, Coimbatore, Bangalore, and Mysore 22. 2016 – 2017 ieee base paper free download 23. 2016 – 2017 ieee titles free download 24. best ieee projects in affordable cost 25. ieee projects free download 26. 2017 data mining projects 27. 2017 ieee projects on data mining 28. 2017 final year data mining projects 29. 2017 data mining projects for b.e 30. 2017 data mining projects for m.e 31. 2017 latest data mining projects 32. latest data mining projects 33. latest data mining projects in java 34. data mining projects in weka tool 35. data mining in intrusion detection system 36. intrusion detection system using data mining 37. intrusion detection system using data mining ppt 38. intrusion detection system using data mining technique 39. data mining approaches for intrusion detection 40. data mining in ranking system using weka tool 41. data mining projects using weka 42. data mining in bioinformatics using weka 43. data mining using weka tool 44. data mining tool weka tutorial 45. data mining abstract 46. data mining base paper 47. data mining research papers 2016 - 2017 48. 2016 - 2017 data mining research papers 49. 2017 data mining research papers 50. data mining IEEE Projects 52. data mining and text mining ieee projects 53. 2017 text mining ieee projects 54. text mining ieee projects 55. ieee projects in web mining 56. 2017 web mining projects 57. 2017 web mining ieee projects 58. 2017 data mining projects with source code 59. 2017 data mining projects for final year students 60. 2017 data mining projects in java 61. 2017 data mining projects for students
Views: 14518 InnovationAdsOfIndia
Part of Speech Tagging - Natural Language Processing With Python and NLTK p.4
 
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Part of Speech tagging does exactly what it sounds like, it tags each word in a sentence with the part of speech for that word. This means it labels words as noun, adjective, verb, etc. PoS tagging also covers tenses of the parts of speech. This is normally quite the challenge, but NLTK makes this pretty darn simple! sample code: http://pythonprogramming.net http://hkinsley.com https://twitter.com/sentdex http://sentdex.com http://seaofbtc.com
Views: 120229 sentdex
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: 82174 sentdex
JavaFx Tutorial For Beginners 5 - Installing JavaFX Scene Builder
 
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Install Scene Builder for Windows. Download/Install From Here (Windows Installer (x64)) - http://gluonhq.com/open-source/scene-builder/ Set Scene Builder path to executable in Intellij. File - Settings - Languages And Frameworks - JavaFx By default mine installed under C:\Users\computer_name\AppData\Local\SceneBuilder\ In this JavaFx Tutorial For Beginners video I will show How to Install JavaFX Scene Builder. JavaFX Scene Builder is a visual layout tool that lets users quickly design JavaFX application user interfaces, without coding. Scene Builder works with the JavaFX ecosystem – official controls, community projects. JavaFX Scene Builder Enables designing user interface screens by simply dragging and positioning GUI components from a palette onto a scene. it Generates files in FXML format that can be used within a project in any IDE such as NetBeans or Eclipse. JavaFX Scene Builder Can be used to create GUI for desktop and Web applications. -------------------Online Courses to learn---------------------------- 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: 122519 ProgrammingKnowledge
Evaluating Text Extraction: Apache Tika's™ New Tika-Eval Module - Tim Allison, The MITRE Corporation
 
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Evaluating Text Extraction: Apache Tika's™ New Tika-Eval Module - Tim Allison, The MITRE Corporation Text extraction tools are essential for obtaining the textual content and metadata of computer files for use in a wide variety of applications, including search and natural language processing tools. Techniques and tools for evaluating text extraction tools are missing from academia and industry. Apache Tika™ detects file types and extracts metadata and text from many file types. Tika is a crucial component in a wide variety of tools, including Solr™, Nutch™, Alfresco, Elasticsearch and Sleuth Kit®/Autopsy®. In this talk, we will give an overview of the new tika-eval module that allows developers to evaluate Tika and other content extraction systems. This talk will end with a brief discussion of the results of taking this evaluation methodology public and evaluating Tika on large batches of public domain documents on a public vm over the last two years. About Tim Allison Tim has been working in natural language processing since 2002. In recent years, his focus has shifted to advanced search and content/metadata extraction. Tim is committer and PMC member on Apache PDFBox (since September 2016), and on Apache POI and Apache Tika since (July, 2013). Tim holds a Ph.D. in Classical Studies from the University of Michigan, and in a former life, he was a professor of Latin and Greek.
Views: 2049 The Linux Foundation
Topic Analysis Using Mallet
 
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This demonstrator shows a the Mallet topic analysis tool being invoked through Rappture. After the analysis has been run, we save the results, then view them in Gnumeric, a spreadsheet tool. Screen Cast produced 12/8/2011.
Views: 2442 Project Bamboo
How to Install Java JDK on Windows 10 ( with JAVA_HOME )
 
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In this video I am going to show you How to install Java JDK on Windows 10 ( with JAVA_HOME ). Java installer .msi file comes with JRE and JDK. Java JDK Installation for Microsoft Windows (64-bit). JDK stands for Java SE Development Kit. JRE stands for Java Runtime Environment. 1. Download Java Open your web browser Type URL: http://www.oracle.com/technetwork/java/javase/downloads/index.html to go to Oracle download page Click on button “ JDK download ” for Java SE update 4. This will lead you JDK download page http://www.oracle.com/technetwork/java/javase/downloads/jdk-7u4-downloads-1591156.html Accept oracle license agreement Find and click on the correct jdk download link right for your operating system to download Save the file to disk 2. Install Java Double click to run the download file Just follow the prompt in Installer window #Javatutorialforbeginners #Javatutorial #Javaprogramming #Javaprogrammingtutorial #Javabasicsforbeginners -------------------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: 1312530 ProgrammingKnowledge
How to use WEKA software for data mining tasks
 
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In this video, I'll guide you how to use WEKA software for preprocessing, classifying, clustering, association. WEKA is a collection of machine learning algorithms for performing data mining tasks. #RanjiRaj #WEKA #DataMining Follow me on Instagram 👉 https://www.instagram.com/reng_army/ Visit my Profile 👉 https://www.linkedin.com/in/reng99/ Support my work on Patreon 👉 https://www.patreon.com/ranjiraj Get WEKA from here : http://www.cs.waikato.ac.nz/ml/weka/
Views: 18703 Ranji Raj
Hotel Review Sentiment Analysis
 
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Analyze customer reviews and feedbacks to find out the best hotels for distinct locations. In this solution, customer sentiment analysis is done to gain meaningful insights and pick up the hotels which are providing the best experience to their customers.
Views: 126 Advaiya
Edward Bullen: Building a ChatBot with Python, NLTK and scikit | PyData London 2017
 
01:31:09
Filmed at PyData 2017 Introducing the basics of Natural Language Processing using Python NLTK and Machine Learning packages to classify language in order to create a simple Q&A bot. Working code samples and a basic ChatBot framework (written in Python) will be provided and explained so that a simple Q&A bot that learns from previous experience and responds to questions with appropriate answers can be created. In this talk we will cover: Build a basic ChatBot Framework using core Python and a SQL database. Demonstrate and experiment with a Learning-by-Example bot using ranking functions in Python and SQL to get some basic chat functionality working. Introduce the Python NLTK to extract features from the chat sentences and words stored in the chatbot database. Work through a feature engineering example using NLTK and Sci-Kit and Numpy to show how we can classify sentences using Supervised Learning and estimate the accuracy of our classification model. Apply the sentence classification ML model to our chatbot engine to target responses more accurately. Prerequisites Attendees will need: + Anaconda for Python 3.5 or 3.6 + NLTK (Python Natural Language Toolkit - pip install nltk) + The Stanford Java CoreNLP Parser (https://stanfordnlp.github.io/CoreNLP/ or wget http://nlp.stanford.edu/software/stanford-corenlp-full-2016-10-31.zip and un-zip) + Java rel 8 Theoretically all of this could be installed on the day but it would just help to save time by preparing in advance. Most of what I am demonstrating will probably work against Python 2.7, but it hasn’t been tested with 2.7. 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. We aim to be an accessible, community-driven conference, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.
Views: 40184 PyData
WordNet  - Natural Language Processing With Python and NLTK p.10
 
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Part of the NLTK Corpora is WordNet. I wouldn't totally classify WordNet as a Corpora, if anything it is really a giant Lexicon, but, either way, it is super useful. With WordNet we can do things like look up words and their meaning according to their parts of speech, we can find synonyms, antonyms, and even examples of the word in use. 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: 69266 sentdex
SAP HANA Academy - HANA Native Development Workshop: Server-Side Java Script
 
24:09
In this series of fifteen videos, Thomas Jung will walk you through creating a web application using the native development toolkit in the SAP HANA 1.0 SP5 release. In this ninth exercise, we see how to utilize the embedded Java Script virtual machine to create server-side functions to customize our application. For more information visit http://academy.saphana.com/
Views: 2812 SAP Technology
Installing the Google Cloud Tools for Eclipse Plugin
 
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This video covers installing the Google Cloud Tools for Eclipse plugin and the Cloud Tools App Engine Components needed for the plugin.
Views: 8634 Brandon Donnelson
Hello World - GWT Tutorial (Google Web Toolkit)
 
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This GWT tutorial for beginners builds a Hello, World web app. We'll use the Eclipse development environment with Google's plugin for it. The tutorial will show you how to set up your app's manifest file, and how to launch a basic application that prints a simple string "hello world" to the page. Although we're not using Google App Engine (GAE), there is nothing stopping you from launching your own project to the cloud - even if all it does is echo a variable out. As mentioned, GWT is an enterprise level tool, so it is definitely not very well suited for a trivial app such as Hello, World. However, I think this is a good demo of how to start a new project, create new modules, create an HTML host page, override the necessary methods that are important in the life cycle of a GWT application, and so forth. Copyright (c) 2013 Rodrigo Silveira http://www.easylearntutorial.com
Views: 62748 Easy Learn Tutorial
PDF SDK Features
 
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This tutorial shows LEADTOOLS PDF features including TIFF to PDF conversion, PDF text extraction, PDF file properties and more For more information, contact our support department at [email protected]
Building a Text Summarizer Flask App with SpaCy,NLTK,Gensim & Sumy
 
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In this tutorial we will be building a Text Summarizer Flask App [Summaryzer App] with SpaCy,NLTK ,Gensim and Sumy in python and with materialize.css. Check out the Free Course on- Learn Julia Fundamentals http://bit.ly/2QLiLG8 If you liked the video don't forget to leave a like or subscribe. If you need any help just message me in the comments, you never know it might help someone else too. J-Secur1ty JCharisTech ==Get The Data Science Prime App== @ Playstore : http://bit.ly/2LArYQu Follow https://www.facebook.com/jcharistech/ https://github.com/Jcharis/ https://twitter.com/JCharisTech https://jcharistech.wordpress.com/
Views: 594 J-Secur1ty
Web page recommendation based on web usage and domain knowledge
 
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Title: Web page recommendation based on web usage and domain knowledge Domain: Data Mining For more details contact: E-Mail: [email protected] Purchase The Whole Project Kit for Rs 5000%. Project Kit: • 1 Review PPT • 2nd Review PPT • Full Coding with described algorithm • Video File • Full Document Note: *For bull purchase of projects and for outsourcing in various domains such as Java, .Net, .PHP, NS2, Matlab, Android, Embedded, Bio-Medical, Electrical, Robotic etc. contact us. *Contact for Real Time Projects, Web Development and Web Hosting services. *Comment and share on this video and win exciting developed projects for free of cost. Search Terms: 1. 2017 ieee projects 2. latest ieee projects in java 3. latest ieee projects in data mining 4. 2017 – 2018 data mining projects 5. 2017 – 2018 best project center in Chennai 6. best guided ieee project center in Chennai 7. 2017 – 2018 ieee titles 8. 2017 – 2018 base paper 9. 2017 – 2018 java projects in Chennai, Coimbatore, Bangalore, and Mysore 10. time table generation projects 11. instruction detection projects in data mining, network security 12. 2017 – 2018 data mining weka projects 13. 2017 – 2018 b.e projects 14. 2017 – 2018 m.e projects 15. 2017 – 2018 final year projects 16. affordable final year projects 17. latest final year projects 18. best project center in Chennai, Coimbatore, Bangalore, and Mysore 19. 2017 Best ieee project titles 20. best projects in java domain 21. free ieee project in Chennai, Coimbatore, Bangalore, and Mysore 22. 2017 – 2018 ieee base paper free download 23. 2017 – 2018 ieee titles free download 24. best ieee projects in affordable cost 25. ieee projects free download 26. 2017 data mining projects 27. 2017 ieee projects on data mining 28. 2017 final year data mining projects 29. 2017 data mining projects for b.e 30. 2017 data mining projects for m.e 31. 2017 latest data mining projects 32. latest data mining projects 33. latest data mining projects in java 34. data mining projects in weka tool 35. data mining in intrusion detection system 36. intrusion detection system using data mining 37. intrusion detection system using data mining ppt 38. intrusion detection system using data mining technique 39. data mining approaches for intrusion detection 40. data mining in ranking system using weka tool 41. data mining projects using weka 42. data mining in bioinformatics using weka 43. data mining using weka tool 44. data mining tool weka tutorial 45. data mining abstract 46. data mining base paper 47. data mining research papers 2017 - 2018 48. 2017 - 2018 data mining research papers 49. 2017 data mining research papers 50. data mining IEEE Projects 52. data mining and text mining ieee projects 53. 2017 text mining ieee projects 54. text mining ieee projects 55. ieee projects in web mining 56. 2017 web mining projects 57. 2017 web mining ieee projects 58. 2017 data mining projects with source code 59. 2017 data mining projects for final year students 60. 2017 data mining projects in java 61. 2017 data mining projects for students
Graphing Live Twitter Sentiment - Language Processing With Python and NLTK p.21
 
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For a current conclusion to this series, we go ahead and graph our basic sentiment analysis results to a live Matplotlib 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: 36870 sentdex
Webinar: OpenNLP & Solr for Superior Relevance
 
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Apache OpenNLP is a machine learning based toolkit for processing natural language text. OpenNLP can be used with Lucene/Solr to tag words with part-of-speech, produce lemmas (words’ base forms), and to extract named entities (people, places, organizations, etc.). Join Lucene/Solr committer Steve Rowe for a webinar to explore how to improve search relevancy with OpenNLP. This webinar covers: - OpenNLP models: Both training and licensing - Part-of-speech: What is it good for (absolutely/RB something/NN) - Lemmatization versus Stemming - Solr configuration and demonstration of lemmatization and named entity extraction Lucidworks' Fusion platform provides the enterprise-grade capabilities needed to design, develop, and deploy intelligent search apps - at any scale. For additional tips, check out Lucidworks blog: http://lucidworks.com/blog Need advanced search capabilities now? Download Fusion: https://lucidworks.com/download/ Join an upcoming Fusion or Solr training: https://lucidworks.com/resources/solr-training-and-consulting/ Contact Sales for a free consultation: https://lucidworks.com/company/contact/
Views: 3425 Lucidworks
Webinar: ChemAxon technology in KNIME workflow management
 
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KNIME is an open source data analytics, reporting and integration platform. Chemical data analysis and data mining is supported within the KNIME framework through the JChem Extension nodes developed by Infocom Inc. Based around ChemAxon's discovery toolkit we will give an introduction to the technology available via the JChem Extension Nodes in KNIME. The webinar will highlight practical user aspects through real life examples, mainly focusing on virtual library design and analysis, as well as document processing for chemical research.
Views: 1321 ChemAxon
Lingpipe Tutorial | NLP | NER | Introduction to Named Entity Recognition
 
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LingPipe is tool kit for processing text using computational linguistics. Here's a brief tutorial on NER using Lingpipe. I'm walking you through all the methods available in Lingpipe for NER I'm using Eclipse Oxygen with Lingpipe 4.0.1
Views: 469 Everything Q
Project Management System
 
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Title: Project Management System Domain: Real Time Key Features: 1. A project is collection of activities that have defined beginning and end. The outcome of every project is a unique product service or a result .there can be many uncertainties about the outcomes due to the unique nature of the projects. Thereby projects planning need to be done in care prior to beginning of the project. 2. The project management is an art of organizing the components and resources together and defining methods of achieving and resources together and defining method of achieving goals and objectives. The project management can be considered as a combination of planning controlling leading, motivating decision making and communication among group of people and managing available resources to achieve specified goals or objectives. 3. The main purpose of project evaluation is to improve the project design, or to reduce the scope of the project or even terminate the project before the project starts to carry on; or to discover the project problems in the project implementation process; and examine the project the effect after the project had ended. For more details contact: E-Mail: [email protected] Buy Whole Project Kit for Rs 5000%. Project Kit: • 1 Review PPT • 2nd Review PPT • Full Coding with described algorithm • Video File • Full Document Note: *For bull purchase of projects and for outsourcing in various domains such as Java, .Net, .PHP, NS2, Matlab, Android, Embedded, Bio-Medical, Electrical, Robotic etc. contact us. *Contact for Real Time Projects, Web Development and Web Hosting services. *Comment and share on this video and win exciting developed projects for free of cost. Search Terms: 1. 2017 ieee projects 2. latest ieee projects in java 3. latest ieee projects in data mining 4. 2017 – 2018 data mining projects 5. 2017 – 2018 best project center in Chennai 6. best guided ieee project center in Chennai 7. 2017 – 2018 ieee titles 8. 2017 – 2018 base paper 9. 2017 – 2018 java projects in Chennai, Coimbatore, Bangalore, and Mysore 10. time table generation projects 11. instruction detection projects in data mining, network security 12. 2017 – 2018 data mining weka projects 13. 2017 – 2018 b.e projects 14. 2017 – 2018 m.e projects 15. 2017 – 2018 final year projects 16. affordable final year projects 17. latest final year projects 18. best project center in Chennai, Coimbatore, Bangalore, and Mysore 19. 2017 Best ieee project titles 20. best projects in java domain 21. free ieee project in Chennai, Coimbatore, Bangalore, and Mysore 22. 2017 – 2018 ieee base paper free download 23. 2017 – 2018 ieee titles free download 24. best ieee projects in affordable cost 25. ieee projects free download 26. 2017 data mining projects 27. 2017 ieee projects on data mining 28. 2017 final year data mining projects 29. 2017 data mining projects for b.e 30. 2017 data mining projects for m.e 31. 2017 latest data mining projects 32. latest data mining projects 33. latest data mining projects in java 34. data mining projects in weka tool 35. data mining in intrusion detection system 36. intrusion detection system using data mining 37. intrusion detection system using data mining ppt 38. intrusion detection system using data mining technique 39. data mining approaches for intrusion detection 40. data mining in ranking system using weka tool 41. data mining projects using weka 42. data mining in bioinformatics using weka 43. data mining using weka tool 44. data mining tool weka tutorial 45. data mining abstract 46. data mining base paper 47. data mining research papers 2016 - 2017 48. 2017 - 2018 data mining research papers 49. 2017 data mining research papers 50. data mining IEEE Projects 52. data mining and text mining ieee projects 53. 2017 text mining ieee projects 54. text mining ieee projects 55. ieee projects in web mining 56. 2017 web mining projects 57. 2017 web mining ieee projects 58. 2017 data mining projects with source code 59. 2017 data mining projects for final year students 60. 2017 data mining projects in java 61. 2017 data mining projects for students 62. 2017 mini projects on data mining 63. latest mini projects on data mining 64. data mining projects for engineering students 65. cse projects on data mining 66. data mining related ieee projects 67. ieee projects in content mining 68. data mining ieee major projects 69. 2017 ieee projects on data mining with abstract 70. 2017 data mining with abstract 71. data mining projects with source code 72. data mining projects for students with demo 73. data mining projects with source code in java 74. data mining mini projects source code 75. list of mini projects in data mining 76. 2017 data mining mini projects topics 77. 2017 data mining related projects 78. 2017 real time data mining projects 79. 2017 data mining projects titles from IEEE
Views: 6376 InnovationAdsOfIndia