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Python Tutorial - Data extraction from raw text
 
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This tutorial focuses on very basic yet powerful operations in Python, to extract meaningful information from junk data. The overall video is covers these 4 points. 1. Basic string operations for data extraction 2. How to open a text file 3. How to read rows line by line 4. Data extraction from junk Feel free to write to me with suggestions and feedback. Stay connected!
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://blog.tramvm.com/2017/05/recognize-text-from-image-with-python.html Relative videos: 1. Recognize digital screen display https://youtu.be/mKYpd6jx3Ms 2. ORM scanner: https://youtu.be/t66OAXI9mkw 3. Recognize answer sheet with mobile phone: https://youtu.be/82FlPaQ92OU 4. Recognize marked grid with USB camera: https://youtu.be/62P0c8YqVDk 5. Recognize answers sheet with mobile phone: https://youtu.be/xVLC4WdXvhE
Views: 107639 Tram Vo Minh
Parsing Text Files in Python
 
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A short program to read lines from a text file and extract information, patterns, from each line.
Views: 102879 Dominique Thiebaut
Large-scale Text Mining for Biological Data
 
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http://togotv.dbcls.jp/20110307.html#p01  In this video, Goran Nenadic who is a Senior Lecturer (Associate Professor) in the School of Computer Science, University of Manchester and a group leader in the Manchester Interdisciplinary BioCenter talks about text mining from biomedical literature. The talk has been at Workshop on Parallel and Distributed Processing of Large Genome Data organized by GCOE Program: Deciphering Genome Sphere from Genome Big Bang.
Views: 1538 togotv
Advanced Python 2:  Advanced Text Processing
 
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How I use python to auto-generate presentations for these lectures; or how to create presentations like a python nut
Views: 2419 Ryan Krauss
Natural Language Processing (NLP) Tutorial | Data Science Tutorial | Simplilearn
 
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Natural language processing (NLP) is a field of computer science, artificial intelligence and computational linguistics concerned with the interactions between computers and human (natural) languages, and, in particular, concerned with programming computers to fruitfully process large natural language corpora. Python for Data Science Certification Training Course: https://www.simplilearn.com/big-data-and-analytics/python-for-data-science-training?utm_campaign=Data-Science-NLP-6WpnxmmkYys&utm_medium=SC&utm_source=youtube The Data Science with Python course is designed to impart an in-depth knowledge of the various libraries and packages required to perform data analysis, data visualization, web scraping, machine learning, and natural language processing using Python. The course is packed with real-life projects, assignment, demos, and case studies to give a hands-on and practical experience to the participants. Mastering Python and using its packages: The course covers PROC SQL, SAS Macros, and various statistical procedures like PROC UNIVARIATE, PROC MEANS, PROC FREQ, and PROC CORP. You will learn how to use SAS for data exploration and data optimization. Mastering advanced analytics techniques: The course also covers advanced analytics techniques like clustering, decision tree, and regression. The course covers time series, it's modeling, and implementation using SAS. As a part of the course, you are provided with 4 real-life industry projects on customer segmentation, macro calls, attrition analysis, and retail analysis. Who should take this course? There is a booming demand for skilled data scientists across all industries that make this course suited for participants at all levels of experience. We recommend this Data Science training especially for the following professionals: 1. Analytics professionals who want to work with Python 2. Software professionals looking for a career switch in the field of analytics 3. IT professionals interested in pursuing a career in analytics 4. Graduates looking to build a career in Analytics and Data Science 5. Experienced professionals who would like to harness data science in their fields 6. Anyone with a genuine interest in the field of Data Science For more updates on courses and tips follow us on: - Facebook : https://www.facebook.com/Simplilearn - Twitter: https://twitter.com/simplilearn Get the android app: http://bit.ly/1WlVo4u Get the iOS app: http://apple.co/1HIO5J0
Views: 26078 Simplilearn
Introduction to bash for data analysis
 
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For absolute beginners. Using the command-line/shell/terminal for basic data analysis. This video covers how to find the terminal, navigating around the file system, looking at files, editing files, and even using piping to string together different commands and unlock the power of bash. The code is at http://omgenomics.com/bash-intro
Views: 9010 OMGenomics
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: 457263 Brandon Weinberg
Natural Language Processing (NLP): Text Clearing
 
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https://drive.google.com/open?id=1yRTuRPLNpLQRI1zEcq9Gx3N6WTcBCqMP What is Machine Learning? Machine learning is a field of computer science that uses statistical techniques to give computer systems the ability to "learn" (e.g., progressively improve performance on a specific task) with data, without being explicitly programmed. Machine learning is closely related to (and often overlaps with) computational statistics, which also focuses on prediction-making through the use of computers. It has strong ties to mathematical optimization, which delivers methods, theory and application domains to the field. Machine learning is sometimes conflated with data mining, where the latter subfield focuses more on exploratory data analysis and is known as unsupervised learning. You should check this video tutorial to easily download Anaconda Navigator for Python Distribution. https://youtu.be/4v7Uke37QGs First of all, you have to download Anaconda Navigator Distribution for Python. For this go to this link and download for your computer depending on your operating system, Windows, Linux or Mac. https://www.anaconda.com/download/ We have used Python 3.6 Version for our course. So you should download that to cope up with us. Data Proessing Complete Playlist: https://www.youtube.com/playlist?list... The next video: https://www.youtube.com/watch?v=RaC85... 1/How can we Master Machine Learning on Python? 2/How can we Have a great intuition of many Machine Learning models? 3/How can we Make accurate predictions? 4/How can we Make powerful analysis? 5/How can we Make robust Machine Learning models? 6/How can we Create strong added value to your business? 7/How do we Use Machine Learning for personal purpose? 8/How can we Handle specific topics like Reinforcement Learning, NLP and Deep Learning? 9/How can we Handle advanced techniques like Dimensionality Reduction? 10/How do we Know which Machine Learning model to choose for each type of problem? 11/How can we Build an army of powerful Machine Learning models and know how to combine them to solve any problem? Subscribe to our channel to get video updates. সাবস্ক্রাইব করুন আমাদের চ্যানেলেঃ https://www.youtube.com/channel/UC50C... Follow us on Facebook: https://www.facebook.com/Planeter.Ban... Follow us on Instagram: https://www.instagram.com/planeter.ba... Follow us on Twitter: https://www.twitter.com/planeterbd Our Website: https://www.planeterbd.com For More Queries: [email protected] #machinelearning #bigdata #ML #DataScience #DataSet #XY #DeepLearning #robotics #রবোটিক্স #প্ল্যনেটার #Planeter #ieeeprotocols #DataProcessing #SimpleLinearRegression #MultiplelinearRegression #PolynomialRegression #SupportVectorRegression(SVR) #DecisionTreeRegression #RandomForestRegression #Evaluation #Regression #Models #MachineLearningClassificatioModels #LogisticRegression #machinelearnigcourse #machinelearningcoursebangla #machinelearningforbeginners #banglamachinelearning #artificialintelligence #machinelearningtutorials #machinelearningcrashcourse #imageprocessing #SpyderIDE #BestBanglaMachineLearningTutorialSeries #ML #MachineLearning
Views: 122 Planeter
PDFix - The Powerful PDF API
 
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The PDFix SDK is available on Mac OS X, Windows, Linux, iOS, Android platforms. Integrate our API into your applications by using C++, Java, C# or .NET Framework Standard PDF Featues: View, Edit, Render, Comment, Print, Search, Sign. Extract Data, Texts, Images and Tables. Convert PDF to HTML, XML, CVS, JSON. Fill Forms, Convert PDF Form to HTML Forms. Add Tags, Make Accessible, Convert PDF to PDF/UA Logical Content Extraction and Conversion: Document Layout and Structure Recognition. Intelligent Data Extraction. Text, Images, Charts, Tables, Lists Extraction. HTML, HTMl5, JSON, Word, Excel, CSV, XML Conversions. PDF Structured Data Scraping or Mining Convert PDF files to HTML: PDF to HTML conversion in Original Fixed layout or Responsive layout with Content Reflow. Conversion to HTML with or without external references. PDF Document JavaScript support. HTML5, JavaScript, CSS3 support. Embed PDF into Web page PDF Forms to HTML Forms: True PDF Form experience with Field Validation and Calculation. Form Field Flattening and Signing. Native HTML form support. Inputs, Dropdown lists, Checkboxes, Radio buttons PDF to CSV: Detect tables borders. Detect table colums and rows. Extract tables into CSV output PDF to XML: Convert PDF files into XML. Manipulate the data as required. Custom conversion configurations Add Tags to PDF: Simple extraction of text and graphics for pasting into other applications. Processing text for such purposes as searching, indexing, and spell-checking. Making content accessible to people who rely on assistive technology Make your PDF files Accessible: PDF/UA Compiliance. Make PDF Files Accessible. Add Tags to PDF Files. Decrease PDF Remediation time and costs. Follow Accessibility Standards, Laws and regulations PDF Data Scraping: Search Text inside PDFs. Detect and Export Tables. Extract Annotations. Use Regular Expression, Pattern Matching
Views: 69 Team PDFix
Large Scale Processing of Unstructured Text
 
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Suneel Marthi, Red Hat
Views: 292 DataWorks Summit
Natural Language processing: More on text cleaning
 
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https://drive.google.com/open?id=1yRTuRPLNpLQRI1zEcq9Gx3N6WTcBCqMP What is Machine Learning? Machine learning is a field of computer science that uses statistical techniques to give computer systems the ability to "learn" (e.g., progressively improve performance on a specific task) with data, without being explicitly programmed. Machine learning is closely related to (and often overlaps with) computational statistics, which also focuses on prediction-making through the use of computers. It has strong ties to mathematical optimization, which delivers methods, theory and application domains to the field. Machine learning is sometimes conflated with data mining, where the latter subfield focuses more on exploratory data analysis and is known as unsupervised learning. You should check this video tutorial to easily download Anaconda Navigator for Python Distribution. https://youtu.be/4v7Uke37QGs First of all, you have to download Anaconda Navigator Distribution for Python. For this go to this link and download for your computer depending on your operating system, Windows, Linux or Mac. https://www.anaconda.com/download/ We have used Python 3.6 Version for our course. So you should download that to cope up with us. Data Proessing Complete Playlist: https://www.youtube.com/playlist?list... The next video: https://www.youtube.com/watch?v=RaC85... 1/How can we Master Machine Learning on Python? 2/How can we Have a great intuition of many Machine Learning models? 3/How can we Make accurate predictions? 4/How can we Make powerful analysis? 5/How can we Make robust Machine Learning models? 6/How can we Create strong added value to your business? 7/How do we Use Machine Learning for personal purpose? 8/How can we Handle specific topics like Reinforcement Learning, NLP and Deep Learning? 9/How can we Handle advanced techniques like Dimensionality Reduction? 10/How do we Know which Machine Learning model to choose for each type of problem? 11/How can we Build an army of powerful Machine Learning models and know how to combine them to solve any problem? Subscribe to our channel to get video updates. সাবস্ক্রাইব করুন আমাদের চ্যানেলেঃ https://www.youtube.com/channel/UC50C... Follow us on Facebook: https://www.facebook.com/Planeter.Ban... Follow us on Instagram: https://www.instagram.com/planeter.ba... Follow us on Twitter: https://www.twitter.com/planeterbd Our Website: https://www.planeterbd.com For More Queries: [email protected] #machinelearning #bigdata #ML #DataScience #DataSet #XY #DeepLearning #robotics #রবোটিক্স #প্ল্যনেটার #Planeter #ieeeprotocols #DataProcessing #SimpleLinearRegression #MultiplelinearRegression #PolynomialRegression #SupportVectorRegression(SVR) #DecisionTreeRegression #RandomForestRegression #Evaluation #Regression #Models #MachineLearningClassificatioModels #LogisticRegression #machinelearnigcourse #machinelearningcoursebangla #machinelearningforbeginners #banglamachinelearning #artificialintelligence #machinelearningtutorials #machinelearningcrashcourse #imageprocessing #SpyderIDE #BestBanglaMachineLearningTutorialSeries #ML #MachineLearning
Views: 61 Planeter
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: 100493 Siraj Raval
How to extract text from an image in python | pytesseract | Image to text processing
 
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In this tutorial, we shall demonstrate you how to extract texts from any image in python. So we shall write a program in python using the module pytesseract that will extract text from any image like .jpg, .jpeg, .png etc. Please subscribe to my youtube channel for such tutorials Watch the same tutorial on how to extract text from an image in Linux below: https://youtu.be/gLUQ8uaaw8A Please watch the split a file by line number here: https://youtu.be/ADRmbu3puCg Split utility in Linux/Unix : to break huge file into small pieces https://www.youtube.com/watch?v=ADRmbu3puCg How to keep sessions alive in terminal/putty infinitely in linux/unix : Useful tips https://www.youtube.com/watch?v=ARIgHdpxaU8 Random value generator and shuffling in python https://www.youtube.com/watch?v=AKwnQQ8TBBM Intro to class in python https://www.youtube.com/watch?v=E6kKZXHS5hM Lists, tuples, dictionary in python https://www.youtube.com/watch?v=Axea1CSewzc Python basic tutorial for beginners https://www.youtube.com/watch?v=_JyjbZc0euY Python basics tutorial for beginners part 2 -variables in python https://www.youtube.com/watch?v=ZlsptvP69NU Vi editor basic to advance part 1 https://www.youtube.com/watch?v=vqxQx-NNyFM Vi editor basic to advance part 2 https://www.youtube.com/watch?v=OWKp2DLaFyY Keyboard remapping in linux, switching keys as per your own choice https://www.youtube.com/watch?v=kJz7uKDyZjs How to install/open an on sceen keyboard in Linux/Unix system https://www.youtube.com/watch?v=d71i9SZX6ck Python IDE for windows , linux and mac OS https://www.youtube.com/watch?v=-tG54yoDs68 How to record screen or sessions in Linux/Unix https://www.youtube.com/watch?v=cx59c15-c8s How to download and install PAGE GUI builder for python https://www.youtube.com/watch?v=dim725Px2hM Create a basic Login page in python using GUI builder PAGE https://www.youtube.com/watch?v=oCAWWUhwEUQ Working with RadioButton in python in PAGE builder https://www.youtube.com/watch?v=YJbQvpzJDr4 Basic program on Multithreading in python using thread module https://www.youtube.com/watch?v=RGm3989ekAc
Views: 24823 LinuxUnixAix
Tutorial Running Docker in Linux Python FLask Services API Machine Learning Text Classification
 
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Download Here For Project : https://github.com/oottoohh/SkripsiProject Tutorial For Install MongoDB : https://medium.com/@sandeshkumard/how-to-install-mongodb-on-windows-3938bbf615bf Tutorial For Install Docker on Linux https://medium.com/@Grigorkh/how-to-install-docker-on-ubuntu-16-04-3f509070d29c
Views: 77 ottoh hidayatullah
Learn to Analyze Text Data in Bash Shell and Linux (Course Organization)
 
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1000+ students have taken this innovative project-based data learning course (includes video lectures and an eBook with source codes and data sets) "Learn to Analyze Text Data in Bash Shell and Linux " https://school.scientificprogramming.io/learn-to-analyze-text-data-in-bash-shell-and-linux-video-lectures Can you build a script to count the number of sequences in a Big data consisting hundred thousands of nucleotide sequences in 30 seconds? You may wonder to know, this wouldn't take more a than a few words in Bash! Three simple projects to demonstrate the use of Bash shell in processing csv formatted text data sets. This course starts with some practical bash-based flat file data mining projects involving: University ranking data Facebook data Crime Data There are several examples of practical data mining that will have a flow of importing specific data resources into flat text-type files. Bash can run different programs (grep, sort, sed, and so on) on those files, clean, optimise and extract preliminary views (cut, csvlook, view, cat, head, etc.) of the data. There is one part of data mining, which involves unstructured data and then transforming it into a structured one (awk, shell). A scripting language like Bash can be very useful for doing the transformation.
Text Mining with Node.js - Philipp Burckhardt, Carnegie Mellon University
 
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Text Mining with Node.js - Philipp Burckhardt, Carnegie Mellon University Today, more data is accumulated than ever before. It has been estimated that over 80% of data collected by businesses is unstructured, mostly in the form of free text. The statistical community has developed many tools for analyzing textual data, both in the areas of exploratory data analysis (e.g. clustering methods) and predictive analytics. In this talk, Philipp Burckhardt will discuss tools and libraries that you can use today to perform text mining with Node.js. Creative strategies to overcome the limitations of the V8 engine in the areas of high-performance and memory-intensive computing will be discussed. You will be introduced to how you can use Node.js streams to analyze text in real-time, how to leverage native add-ons for performance-intensive code and how to build command-line interfaces to process text directly from the terminal.
Views: 2647 node.js
PDF Data Extraction and Automation 3.1
 
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Learn how to read and extract PDF data. Whether in native text format or scanned images, UiPath allows you to navigate, identify and use PDF data however you need. Read PDF. Read PDF with OCR.
Views: 131311 UiPath
Log File Frequency Analysis with Python
 
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Information Security professionals often have reason to analyze logs. Whether Red Team or Blue Team, there are countless times that you find yourself using "grep", "tail", "cut", "sort", "uniq", and even "awk"! While these powerful UNIX methods take us far, there is always that time when you want more power! In this webcast, Joff Thyer will discuss using Python regular expressions, and dictionaries to extract useful data for frequency analysis. If you want to learn even more about Python, join Joff for SANS SEC573 - "Automating Information Security with Python" www.sans.org/sec573 Slides available here: https://www.blackhillsinfosec.com/webcast-log-file-frequency-analysis-python/
Import Data and Analyze with Python
 
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Python programming language allows sophisticated data analysis and visualization. This tutorial is a basic step-by-step introduction on how to import a text file (CSV), perform simple data analysis, export the results as a text file, and generate a trend. See https://youtu.be/pQv6zMlYJ0A for updated video for Python 3.
Views: 207918 APMonitor.com
NLP with JavaScript- How to do Sentiment Analysis
 
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Natural Language Processing with JavaScript - Sentiment Analysis In this tutorial we will be learning about how to do sentiment analysis in JavaScript using sentiment.js Package Requirement - npm install sentiment Code For this Video Github: http://bit.ly/2xaxVgU 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 Follow https://www.facebook.com/jcharistech/ https://github.com/Jcharis/ https://twitter.com/JCharisTech https://jcharistech.wordpress.com/
Views: 678 J-Secur1ty
BASH scripting lesson 10 working with CSV files
 
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More videos like this online at http://www.theurbanpenguin.com We now have some more great fun and see how much we can use the shell for; creating reports easily from the command line against CSV files. The script should be quite easy to read now as we use a while loop to read in the CSV file. We change the file delimiter to be the comma and then we have the line that we read in broken up into the schema elements we need. A report then is easy with colours and search ability. This is very usable
Views: 50408 theurbanpenguin
An Introduction to GPU Programming with CUDA
 
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If you can parallelize your code by harnessing the power of the GPU, I bow to you. GPU code is usually abstracted away by by the popular deep learning frameworks, but knowing how it works is really useful. CUDA is the most popular of the GPU frameworks so we're going to add two arrays together, then optimize that process using it. I love CUDA! Code for this video: https://github.com/llSourcell/An_Introduction_to_GPU_Programming Alberto's Winning Code: https://github.com/alberduris/SirajsCodingChallenges/tree/master/Stock%20Market%20Prediction Hutauf's runner-up code: https://github.com/hutauf/Stock_Market_Prediction Please Subscribe! And like. And comment. That's what keeps me going. Follow me: Twitter: https://twitter.com/sirajraval Facebook: https://www.facebook.com/sirajology More learning resources: http://supercomputingblog.com/cuda-tutorials/ http://www.nvidia.com/docs/IO/116711/sc11-cuda-c-basics.pdf https://devblogs.nvidia.com/parallelforall/even-easier-introduction-cuda/ https://developer.nvidia.com/cuda-education-training https://llpanorama.wordpress.com/cuda-tutorial/ https://www.udacity.com/course/intro-to-parallel-programming--cs344 http://lorenabarba.com/gpuatbu/Program_files/Cruz_gpuComputing09.pdf http://cuda-programming.blogspot.nl/p/tutorial.html https://www.cc.gatech.edu/~vetter/keeneland/tutorial-2011-04-14/02-cuda-overview.pdf Join us in the Wizards Slack channel: http://wizards.herokuapp.com/ No, Nvidia did not pay me to make this video lol. I just love CUDA. 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/ 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: 187054 Siraj Raval
Sentiment Analysis in R | Sentiment Analysis of Twitter Data | Data Science Training | Edureka
 
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( Data Science Training - https://www.edureka.co/data-science ) This Sentiment Analysis Tutorial shall give you a clear understanding as to how a Sentiment Analysis machine learning algorithm works in R. Towards the end, we will be streaming data from Twitter and will do a comparison between two football teams - Barcelona and Real Madrid (El Clasico Sentiment Analysis) Below are the topics covered in this tutorial: 1) What is Machine Learning? 2) Why Sentiment Analysis? 3) What is Sentiment Analysis? 4) How Sentiment Analysis works? 5) Sentiment Analysis - El Clasico Demo 6) Sentiment Analysis - Use Cases Subscribe to our channel to get video updates. Hit the subscribe button above. Check our complete Data Science playlist here: https://goo.gl/60NJJS #SentimentAnalysis #Datasciencetutorial #Datasciencecourse #datascience How it Works? 1. There will be 30 hours of instructor-led interactive online classes, 40 hours of assignments and 20 hours of project 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. You will get Lifetime Access to the recordings in the LMS. 4. At the end of the training you will have to complete the project based on which we will provide you a Verifiable Certificate! - - - - - - - - - - - - - - About the Course Edureka's Data Science course will cover the whole data life cycle ranging from Data Acquisition and Data Storage using R-Hadoop concepts, Applying modelling through R programming using Machine learning algorithms and illustrate impeccable Data Visualization by leveraging on 'R' capabilities. - - - - - - - - - - - - - - Why Learn Data Science? Data Science training certifies you with ‘in demand’ Big Data Technologies to help you grab the top paying Data Science job title with Big Data skills and expertise in R programming, Machine Learning and Hadoop framework. After the completion of the Data Science course, you should be able to: 1. Gain insight into the 'Roles' played by a Data Scientist 2. Analyse Big Data using R, Hadoop and Machine Learning 3. Understand the Data Analysis Life Cycle 4. Work with different data formats like XML, CSV and SAS, SPSS, etc. 5. Learn tools and techniques for data transformation 6. Understand Data Mining techniques and their implementation 7. Analyse data using machine learning algorithms in R 8. Work with Hadoop Mappers and Reducers to analyze data 9. Implement various Machine Learning Algorithms in Apache Mahout 10. Gain insight into data visualization and optimization techniques 11. Explore the parallel processing feature in R - - - - - - - - - - - - - - Who should go for this course? The course is designed for all those who want to learn machine learning techniques with implementation in R language, and wish to apply these techniques on Big Data. The following professionals can go for this course: 1. Developers aspiring to be a 'Data Scientist' 2. Analytics Managers who are leading a team of analysts 3. SAS/SPSS Professionals looking to gain understanding in Big Data Analytics 4. Business Analysts who want to understand Machine Learning (ML) Techniques 5. Information Architects who want to gain expertise in Predictive Analytics 6. 'R' professionals who want to captivate and analyze Big Data 7. Hadoop Professionals who want to learn R and ML techniques 8. Analysts wanting to understand Data Science methodologies For more information, Please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll free). Instagram: https://www.instagram.com/edureka_learning/ Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka Customer Reviews: Gnana Sekhar Vangara, Technology Lead at WellsFargo.com, says, "Edureka Data science course provided me a very good mixture of theoretical and practical training. The training course helped me in all areas that I was previously unclear about, especially concepts like Machine learning and Mahout. The training was very informative and practical. LMS pre recorded sessions and assignmemts were very good as there is a lot of information in them that will help me in my job. The trainer was able to explain difficult to understand subjects in simple terms. Edureka is my teaching GURU now...Thanks EDUREKA and all the best. "
Views: 31210 edureka!
First time Weka Use : How to create & load data set in Weka : Weka Tutorial # 2
 
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This video will show you how to create and load dataset in weka tool. weather data set excel file https://eric.univ-lyon2.fr/~ricco/tanagra/fichiers/weather.xls
Views: 39272 HowTo
R - Twitter Mining with R (part 1)
 
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Twitter Mining with R part 1 takes you through setting up a connection with Twitter. This requires a couple packages you will need to install, and creating a Twitter application, which needs to be authorized in R before you can access tweets. We quickly go through this entire process which may take some flexibility on your part so be patient and be ready troubleshoot as details change with updates. Warning: You are going to face challenges setting up the twitter API connection. The steps for this part have been known to change slightly over time for a variety of reasons. Follow the general steps and expect a few errors along the way which you will have to troubleshoot. It is hard to solve these issues remotely from where I am.
Views: 66443 Jalayer Academy
Convert PDF to Text: Python PDFminer example using Python
 
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In this example we converted PDF into text using stanford code. Source code link https://github.com/shakkaist/Python/blob/master/Day2Session2/pdfconverter.py
Views: 14590 RNS Solutions
Time Series Analysis in Python | Time Series Forecasting | Data Science with Python | Edureka
 
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** Python Data Science Training : https://www.edureka.co/python ** This Edureka Video on Time Series Analysis n Python will give you all the information you need to do Time Series Analysis and Forecasting in Python. Below are the topics covered in this tutorial: 1. Why Time Series? 2. What is Time Series? 3. Components of Time Series 4. When not to use Time Series 5. What is Stationarity? 6. ARIMA Model 7. Demo: Forecast Future Subscribe to our channel to get video updates. Hit the subscribe button above. Machine Learning Tutorial Playlist: https://goo.gl/UxjTxm #timeseries #timeseriespython #machinelearningalgorithms - - - - - - - - - - - - - - - - - About the Course Edureka’s Course on Python helps you gain expertise in various machine learning algorithms such as regression, clustering, decision trees, random forest, Naïve Bayes and Q-Learning. Throughout the Python Certification Course, you’ll be solving real life case studies on Media, Healthcare, Social Media, Aviation, HR. During our Python Certification Training, our instructors will help you to: 1. Master the basic and advanced concepts of Python 2. Gain insight into the 'Roles' played by a Machine Learning Engineer 3. Automate data analysis using python 4. Gain expertise in machine learning using Python and build a Real Life Machine Learning application 5. Understand the supervised and unsupervised learning and concepts of Scikit-Learn 6. Explain Time Series and it’s related concepts 7. Perform Text Mining and Sentimental analysis 8. Gain expertise to handle business in future, living the present 9. Work on a Real Life Project on Big Data Analytics using Python and gain Hands on Project Experience - - - - - - - - - - - - - - - - - - - Why learn Python? Programmers love Python because of how fast and easy it is to use. Python cuts development time in half with its simple to read syntax and easy compilation feature. Debugging your programs is a breeze in Python with its built in debugger. Using Python makes Programmers more productive and their programs ultimately better. Python continues to be a favorite option for data scientists who use it for building and using Machine learning applications and other scientific computations. Python runs on Windows, Linux/Unix, Mac OS and has been ported to Java and .NET virtual machines. Python is free to use, even for the commercial products, because of its OSI-approved open source license. Python has evolved as the most preferred Language for Data Analytics and the increasing search trends on python also indicates that Python is the next "Big Thing" and a must for Professionals in the Data Analytics domain. For more information, Please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll free). Instagram: https://www.instagram.com/edureka_learning/ Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka
Views: 63838 edureka!
K Means Clustering Algorithm | K Means Example in Python | Machine Learning Algorithms | Edureka
 
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** Python Training for Data Science: https://www.edureka.co/python ** This Edureka Machine Learning tutorial (Machine Learning Tutorial with Python Blog: https://goo.gl/fe7ykh ) series presents another video on "K-Means Clustering Algorithm". Within the video you will learn the concepts of K-Means clustering and its implementation using python. Below are the topics covered in today's session: 1. What is Clustering? 2. Types of Clustering 3. What is K-Means Clustering? 4. How does a K-Means Algorithm works? 5. K-Means Clustering Using Python Machine Learning Tutorial Playlist: https://goo.gl/UxjTxm Subscribe to our channel to get video updates. Hit the subscribe button above. How it Works? 1. This is a 5 Week Instructor led Online Course,40 hours of assignment and 20 hours of project work 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 be working on a real time project for which we will provide you a Grade and a Verifiable Certificate! - - - - - - - - - - - - - - - - - About the Course Edureka's Python Online Certification Training will make you an expert in Python programming. It will also help you learn Python the Big data way with integration of Machine learning, Pig, Hive and Web Scraping through beautiful soup. During our Python Certification training, our instructors will help you: 1. Programmatically download and analyze data 2. Learn techniques to deal with different types of data – ordinal, categorical, encoding 3. Learn data visualization 4. Using I python notebooks, master the art of presenting step by step data analysis 5. Gain insight into the 'Roles' played by a Machine Learning Engineer 6. Describe Machine Learning 7. Work with real-time data 8. Learn tools and techniques for predictive modeling 9. Discuss Machine Learning algorithms and their implementation 10. Validate Machine Learning algorithms 11. Explain Time Series and its related concepts 12. Perform Text Mining and Sentimental analysis 13. Gain expertise to handle business in future, living the present - - - - - - - - - - - - - - - - - - - Why learn Python? Programmers love Python because of how fast and easy it is to use. Python cuts development time in half with its simple to read syntax and easy compilation feature. Debugging your programs is a breeze in Python with its built in debugger. Using Python makes Programmers more productive and their programs ultimately better. Python continues to be a favorite option for data scientists who use it for building and using Machine learning applications and other scientific computations. Python runs on Windows, Linux/Unix, Mac OS and has been ported to Java and .NET virtual machines. Python is free to use, even for the commercial products, because of its OSI-approved open source license. Python has evolved as the most preferred Language for Data Analytics and the increasing search trends on python also indicates that Python is the next "Big Thing" and a must for Professionals in the Data Analytics domain. For more information, Please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll free). Instagram: https://www.instagram.com/edureka_learning/ Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka Customer Review Sairaam Varadarajan, Data Evangelist at Medtronic, Tempe, Arizona: "I took Big Data and Hadoop / Python course and I am planning to take Apache Mahout thus becoming the "customer of Edureka!". Instructors are knowledge... able and interactive in teaching. The sessions are well structured with a proper content in helping us to dive into Big Data / Python. Most of the online courses are free, edureka charges a minimal amount. Its acceptable for their hard-work in tailoring - All new advanced courses and its specific usage in industry. I am confident that, no other website which have tailored the courses like Edureka. It will help for an immediate take-off in Data Science and Hadoop working."
Views: 34790 edureka!
Why you should use Python 3 for text processing
 
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David Mertz Python is a great language for text processing. Each new version of Python--but especially the 3.x series--has enhanced this strength of the language. String (and byte) objects have grown some handy methods and some built-in functions ha
Views: 9791 Next Day Video
Weka Tutorial 02: Data Preprocessing 101 (Data Preprocessing)
 
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This tutorial demonstrates various preprocessing options in Weka. However, details about data preprocessing will be covered in the upcoming tutorials.
Views: 168075 Rushdi Shams
Data Mining #Facebook
 
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This is how to mine personal Data from facebook. https://satoshibox.com/3z6dwcvsks5fnxahns5w3z3d facebook,data mining,data,facebook data mining,data mining facebook,data mining for facebook,facebook data mining using r programming,data mining facebook using r,facebook data leak,data mining facebook using curl,data mining facebook using linux,mining data on facebook,data mining for facebook using graph api,mining data on facebook with python,mining facebook posts,facebook api,data science
Views: 34 IT- Guy
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
Introduction to Natural Language Processing in Tamil | NLP
 
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Natural language processing (Wikipedia): “Natural language processing (NLP) is a field of computer science, artificial intelligence, and computational linguistics concerned with the interactions between computers and human (natural) languages
Views: 3113 Abu Tech
Python Tutorial: Anaconda - Installation and Using Conda
 
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In this Python Tutorial, we will be learning how to install Anaconda by Continuum Analytics. Anaconda is a data science platform that comes with a lot of useful features right out of the box. Many people find that installing Python through Anaconda is much easier than doing so manually. Also, we will look at Conda. Conda is Continuum's package, dependency and environment manager. Let's get started. Anaconda Download Page: https://www.anaconda.com/download/ 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/ #Python
Views: 581911 Corey Schafer
Natural Language Processing with Polyglot - Installation & Intro
 
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In this tutorial we will be learning about how to do natural language processing with Polyglot in python. Polyglot is a natural language pipeline that supports massive multilingual applications.Polyglot has a similar learning curve with TextBlob making it easier to pick up quickly if you know TextBlob. Code Github :http://bit.ly/2ElZOYH 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 Learn Julia App== @ Playstore : http://bit.ly/2NOiV2u @ Amazon :https://amzn.to/2OYOQdd Follow https://www.facebook.com/jcharistech/ https://github.com/Jcharis/ https://twitter.com/JCharisTech https://jcharistech.wordpress.com/ Written Tutorial https://jcharistech.wordpress.com/2018/12/10/introduction-to-natural-language-processing-with-polyglot/
Views: 325 J-Secur1ty
Log File Analysis: Python Log Parsing
 
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In this video we will see python searches in a very simple way. Python is a great utility to do this type of work since you can make many queries or searches in a short time. ---------------------------------------------------------------------------------------- Remember, if you want more information or have questions, suggestions, leave a comment below, or visit our site and social networks. ☑️ InfoSecAddicts Website: https://infosecaddicts.com/ ☑️ 🌐 SOCIAL NETWORKS 🌐 Facebook: https://www.facebook.com/InfoSecAddicts/ 📡 Twitter: https://twitter.com/InfoSecAddicts?s=17 Give us a 👍 🎥 Thanks for watching, and I hope you enjoyed the video. 🎥 🙂
Views: 452 InfoSecAddicts
Scammed on ebay... Testing the 56 CORE system!
 
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Thanks so much for Audible for sponsoring this video! Get Your FREE 30 Day Audible Trial Today! Head to http://audible.com/linus or text Linus to 500-500. Enter our competition to win a free 6-month subscription by Tweeting @LinusTech screenshots of your favorite Audio Books! #NewYearNewMe Buy Intel Xeon processors on Amazon: http://geni.us/9deQri Discuss on the forum: https://linustechtips.com/main/topic/890948-scammed-on-ebay-testing-the-56-core-system/ 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: 7063724 Linus Tech Tips
How to use Weka Software for data mining
 
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weka software download link http://filehippo.com/download_weka/ How to install Red Hat Enterprise Linux 6.0 on the VMware Workstation 7 || RedHat link: https://www.youtube.com/watch?v=lLT5jz-iRPI
Views: 249 SD- Creation
Daniel Krasner - High Performance Text Processing with Rosetta
 
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View slideshare presentation here: http://www.slideshare.net/PyData/daniel-krasner-high-performance-text-processing-with-rosetta PyData NYC 2014 This talk covers rapid prototyping of a high performance scalable text processing pipeline development in Python. We demonstrate how Python modules, in particular from the Rosetta library, can be used to analyze, clean, extract features, and finally perform machine learning tasks such as classification or topic modeling on millions of documents. Our style is to build small and simple modules (each with command line interfaces) that use very little memory and are parallelized with the multiprocessing library.
Views: 791 PyData
Server Log Analysis with Pandas
 
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Taavi Burns Use iPython, matplotlib, and Pandas to slice, dice, and visualize your application's behaviour through its logs.
Views: 9622 Next Day Video
WordCloud using Python
 
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This video demonstrates how to create a wordcloud of any given text-corpora/article using wordcloud module in Python. Code here: https://github.com/nikhilkumarsingh/wordcloud-example More awesome topics covered here: WhatsApp Bot using Twilio and Python: http://bit.ly/2JmZaNG Discovering Hidden APIs: http://bit.ly/2umeMHb RegEx in Python: http://bit.ly/2Hhtd6L Introduction to Numpy: http://bit.ly/2RZMxvO Introduction to Matplotlib: http://bit.ly/2UzwfqH Introduction to Pandas: http://bit.ly/2GkDvma Intermediate Python: http://bit.ly/2sdlEFs Functional Programming in Python: http://bit.ly/2FaEFB7 Python Package Publishing: http://bit.ly/2SCLkaj Multithreading in Python: http://bit.ly/2RzB1GD Multiprocessing in Python: http://bit.ly/2Fc9Xrp Parallel Programming in Python: http://bit.ly/2C4U81k Concurrent Programming in Python: http://bit.ly/2BYiREw Dataclasses in Python: http://bit.ly/2SDYQub Exploring YouTube Data API: http://bit.ly/2AvToSW Jupyter Notebook (Tips, Tricks and Hacks): http://bit.ly/2At7x3h Decorators in Python: http://bit.ly/2sdloX0 Inside Python: http://bit.ly/2Qr9gLG Exploring datetime: http://bit.ly/2VyGZGN Computer Vision for noobs: http://bit.ly/2RadooB Python for web: http://bit.ly/2SEZFmo Awesome Linux Terminal: http://bit.ly/2VwdTYH Tips, tricks, hacks and APIs: http://bit.ly/2Rajllx Optical Character Recognition: http://bit.ly/2LZ8IfL Facebook Messenger Bot Tutorial: http://bit.ly/2BYjON6 #python #wordcloud #pil
Views: 13054 Indian Pythonista
Basic Python Tutorial 23 - Reading a text file
 
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Learn how to use multiple methods to read a text file in python. Investary Website -- http://www.investary.org Twitter - http://www.twitter.com/investary Facebook - http://www.facebook.com/investary Questions, comments, feedback? Leave it in the comments section. Also if you can please subscribe and like this video, it will help me tremendously.
Views: 168199 investary
How to read Excel files with Python (xlrd tutorial)
 
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Learn how to read out data from an Excel document using the xlrd Python module. The xlsx and xls file formats are supported. xlrd docs: http://www.lexicon.net/sjmachin/xlrd.html Type Numbers: 0 - XL_CELL_EMPTY 1 - XL_CELL_TEXT 2 - XL_CELL_NUMBER 3 - XL_CELL_DATE 4 - XL_CELL_BOOLEAN 5 - XL_CELL_ERROR 6 - XL_CELL_BLANK
Views: 195283 triforcelink