Udemy - Hands On Natural Language Processing (NLP) using Python [Course Drive]

seeders: 7
leechers: 27
updated:
Download torrent
Added by coursedrive in Other > Tutorials
Download Fast Safe Anonymous
movies, software, shows...
  • Downloads: 140
  • Language: English

Files

Hands On Natural Language Processing (NLP) using Python Hands On Natural Language Processing (NLP) using Python 6. NLP Core
  • 25. LSA in Python Part 1.mp4 (295.6 MB)
  • 1. Installing NLTK in Python.mp4 (29.3 MB)
  • 1. Installing NLTK in Python.srt (5.3 KB)
  • 1. Installing NLTK in Python.vtt (4.7 KB)
  • 2. Tokenizing Words and Sentences.mp4 (74.6 MB)
  • 2. Tokenizing Words and Sentences.srt (5.3 KB)
  • 2. Tokenizing Words and Sentences.vtt (4.7 KB)
  • 3. How tokenization works - Text.html (1.6 KB)
  • 4. Introduction to Stemming and Lemmatization.mp4 (107.5 MB)
  • 4. Introduction to Stemming and Lemmatization.srt (10.1 KB)
  • 4. Introduction to Stemming and Lemmatization.vtt (8.8 KB)
  • 5. Stemming using NLTK.mp4 (133.5 MB)
  • 5. Stemming using NLTK.srt (8.5 KB)
  • 5. Stemming using NLTK.vtt (7.4 KB)
  • 6. Lemmatization using NLTK.mp4 (76.5 MB)
  • 6. Lemmatization using NLTK.srt (4.5 KB)
  • 6. Lemmatization using NLTK.vtt (3.9 KB)
  • 7. Stop word removal using NLTK.mp4 (139.8 MB)
  • 7. Stop word removal using NLTK.srt (8.6 KB)
  • 7. Stop word removal using NLTK.vtt (7.5 KB)
  • 8. Parts Of Speech Tagging.mp4 (109.1 MB)
  • 8. Parts Of Speech Tagging.srt (7.8 KB)
  • 8. Parts Of Speech Tagging.vtt (6.8 KB)
  • 9. POS Tag Meanings.html (3.3 KB)
  • 10. Named Entity Recognition.mp4 (56.1 MB)
  • 10. Named Entity Recognition.srt (6.8 KB)
  • 10. Named Entity Recognition.vtt (6.0 KB)
  • 11. Text Modelling using Bag of Words Model.mp4 (146.1 MB)
  • 11. Text Modelling using Bag of Words Model.srt (14.7 KB)
  • 11. Text Modelling using Bag of Words Model.vtt (12.8 KB)
  • 12. Building the BOW Model Part 1.mp4 (88.6 MB)
  • 12. Building the BOW Model Part 1.srt (5.4 KB)
  • 12. Building the BOW Model Part 1.vtt (4.8 KB)
  • 13. Building the BOW Model Part 2.mp4 (82.2 MB)
  • 13. Building the BOW Model Part 2.srt (6.0 KB)
  • 13. Building the BOW Model Part 2.vtt (5.3 KB)
  • 14. Building the BOW Model Part 3.mp4 (77.0 MB)
  • 14. Building the BOW Model Part 3.srt (5.7 KB)
  • 14. Building the BOW Model Part 3.vtt (5.0 KB)
  • 15. Building the BOW Model Part 4.mp4 (108.1 MB)
  • 15. Building the BOW Model Part 4.srt (8.4 KB)
  • 15. Building the BOW Model Part 4.vtt (7.4 KB)
  • 16. Text Modelling using TF-IDF Model.mp4 (223.0 MB)
  • 16. Text Modelling using TF-IDF Model.srt (22.1 KB)
  • 16. Text Modelling using TF-IDF Model.vtt (19.2 KB)
  • 17. Building the TF-IDF Model Part 1.mp4 (109.9 MB)
  • 17. Building the TF-IDF Model Part 1.srt (8.2 KB)
  • 17. Building the TF-IDF Model Part 1.vtt (7.2 KB)
  • 18. Building the TF-IDF Model Part 2.mp4 (122.7 MB)
  • 18. Building the TF-IDF Model Part 2.srt (9.4 KB)
  • 18. Building the TF-IDF Model Part 2.vtt (8.2 KB)
  • 19. Building the TF-IDF Model Part 3.mp4 (109.8 MB)
  • 19. Building the TF-IDF Model Part 3.srt (8.4 KB)
  • 19. Building the TF-IDF Model Part 3.vtt (7.3 KB)
  • 20. Building the TF-IDF Model Part 4.mp4 (64.6 MB)
  • 20. Building the TF-IDF Model Part 4.srt (5.3 KB)
  • 20. Building the TF-IDF Model Part 4.vtt (4.6 KB)
  • 21. Understanding the N-Gram Model.mp4 (259.2 MB)
  • 21. Understanding the N-Gram Model.srt (27.1 KB)
  • 21. Understanding the N-Gram Model.vtt (23.5 KB)
  • 22. Building Character N-Gram Model.mp4 (185.7 MB)
  • 22. Building Character N-Gram Model.srt (20.2 KB)
  • 22. Building Character N-Gram Model.vtt (17.6 KB)
  • 23. Building Word N-Gram Model.mp4 (160.5 MB)
  • 23. Building Word N-Gram Model.srt (14.8 KB)
  • 23. Building Word N-Gram Model.vtt (12.9 KB)
  • 24. Understanding Latent Semantic Analysis.mp4 (194.5 MB)
  • 24. Understanding Latent Semantic Analysis.srt (19.3 KB)
  • 24. Understanding Latent Semantic Analysis.vtt (16.8 KB)
  • 25. LSA in Python Part 1.srt (25.9 KB)
  • 25. LSA in Python Part 1.vtt (22.3 KB)
  • 26. LSA in Python Part 2.mp4 (190.2 MB)
  • 26. LSA in Python Part 2.srt (14.9 KB)
  • 26. LSA in Python Part 2.vtt (12.9 KB)
  • 27. Word Synonyms and Antonyms using NLTK.mp4 (118.0 MB)
  • 27. Word Synonyms and Antonyms using NLTK.srt (13.2 KB)
  • 27. Word Synonyms and Antonyms using NLTK.vtt (11.4 KB)
  • 28. Word Negation Tracking in Python Part 1.mp4 (90.7 MB)
  • 28. Word Negation Tracking in Python Part 1.srt (12.7 KB)
  • 28. Word Negation Tracking in Python Part 1.vtt (11.0 KB)
  • 29. Word Negation Tracking in Python Part 2.mp4 (58.6 MB)
  • 29. Word Negation Tracking in Python Part 2.srt (8.1 KB)
  • 29. Word Negation Tracking in Python Part 2.vtt (7.1 KB)
  • Course Downloaded from coursedrive.org.txt (0.5 KB)
  • Visit Coursedrive.org.url (0.1 KB)
    • 1. Introduction to the Course
    • 1. What is NLP.mp4 (75.7 MB)
    • 1. What is NLP.srt (7.7 KB)
    • 1. What is NLP.vtt (6.7 KB)
    • 2. Getting the Course Resources.mp4 (18.2 MB)
    • 2. Getting the Course Resources.srt (2.1 KB)
    • 2. Getting the Course Resources.vtt (1.8 KB)
    • 3. Getting the Course Resources - Text.html (0.6 KB)
    2. Getting the required softwares
    • 1. Installing Anaconda Python.mp4 (33.4 MB)
    • 1. Installing Anaconda Python.srt (4.5 KB)
    • 1. Installing Anaconda Python.vtt (3.9 KB)
    • 2. Installing Anaconda Python - Text.html (0.7 KB)
    • 3. A tour of Spyder IDE.mp4 (46.8 MB)
    • 3. A tour of Spyder IDE.srt (6.1 KB)
    • 3. A tour of Spyder IDE.vtt (5.3 KB)
    • 4. How to take this course.html (1.6 KB)
    3. Python Crash Course
    • 1. Variables and Operations in Python.mp4 (60.3 MB)
    • 1. Variables and Operations in Python.srt (9.5 KB)
    • 1. Variables and Operations in Python.vtt (8.3 KB)
    • 2. Conditional Statements.mp4 (63.8 MB)
    • 2. Conditional Statements.srt (7.0 KB)

    • Description

      Hands On Natural Language Processing (NLP) using Python

      Learn Natural Language Processing ( NLP ) & Text Mining by creating text classifier, article summarizer, and many more.






      What you'll learn

      • Understand the various concepts of natural language processing along with their implementation
      • Build natural language processing based applications
      • Learn about the different modules available in Python for NLP
      • Create personal spam filter or sentiment predictor
      • Create personal text summarizer

      Requirements

      • Basic Programming Experience in any language
      • Concept of Object Oriented Programming
      • Knowledge of Basic to Intermediate Mathematics
      • Knowledge of Matrix operations

      Description

      In this course you will learn the various concepts of natural language processing by implementing them hands on in python programming language. This course is completely project based and from the start of the course the main objective would be to learn all the concepts required to finish the different projects. You will be building a text classifier which you will use to predict sentiments of tweets in real time and you will also be building an article summarizer which will fetch articles from websites and find the summary. Apart from these you will also be doing a lot of mini projects through out the course. So, at the end of the course you will have a deep understanding of NLP and how it is applied in real world.

      Who this course is for:

      • Anyone willing to start a career in data science and natural language processing
      • Anyone willing to learn the concepts of natural language processing by implementing them
      • Anyone willing to learn Sentiment Analysis



Download torrent
8 GB
seeders:7
leechers:27
Udemy - Hands On Natural Language Processing (NLP) using Python [Course Drive]

Trackers

tracker name
udp://tracker.opentrackr.org:1337/announce
udp://tracker.leechers-paradise.org:6969/announce
http://p4p.arenabg.com:1337/announce
udp://9.rarbg.to:2710/announce
udp://9.rarbg.me:2710/announce
udp://exodus.desync.com:6969/announce
udp://open.stealth.si:80/announce
udp://tracker.cyberia.is:6969/announce
udp://tracker.tiny-vps.com:6969/announce
udp://tracker.sbsub.com:2710/announce
udp://retracker.lanta-net.ru:2710/announce
udp://tracker.torrent.eu.org:451/announce
udp://tracker.moeking.me:6969/announce
http://tracker3.itzmx.com:6961/announce
http://tracker1.itzmx.com:8080/announce
µTorrent compatible trackers list

Download torrent
8 GB
seeders:7
leechers:27
Udemy - Hands On Natural Language Processing (NLP) using Python [Course Drive]

Torrent hash: D9289920473F5DEBF673080E8E832D7115EC0773