| 1. Getting the data for Text Classification.mp4 | 62.1 MB | ||
| 1. Getting the data for Text Classification.srt | 7.6 KB | ||
| 1. Getting the data for Text Classification.vtt | 6.7 KB | ||
| 1. Installing Anaconda Python.mp4 | 33.4 MB | ||
| 1. Installing Anaconda Python.srt | 4.5 KB | ||
| 1. Installing Anaconda Python.vtt | 3.9 KB | ||
| 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 | ||
| 1. Introduction to Numpy.mp4 | 280.7 MB | ||
| 1. Introduction to Numpy.srt | 27.1 KB | ||
| 1. Introduction to Numpy.vtt | 23.5 KB | ||
| 1. Introduction to Regular Expressions.mp4 | 62.8 MB | ||
| 1. Introduction to Regular Expressions.srt | 6.1 KB | ||
| 1. Introduction to Regular Expressions.vtt | 5.4 KB | ||
| 1. Setting up Twitter Application.mp4 | 28.3 MB | ||
| 1. Setting up Twitter Application.srt | 5 KB | ||
| 1. Setting up Twitter Application.vtt | 4.3 KB | ||
| 1. Understanding Text Summarization.mp4 | 95.7 MB | ||
| 1. Understanding Text Summarization.srt | 9.8 KB | ||
| 1. Understanding Text Summarization.vtt | 8.5 KB | ||
| 1. Understanding Word Vectors.mp4 | 160.6 MB | ||
| 1. Understanding Word Vectors.srt | 16 KB | ||
| 1. Understanding Word Vectors.vtt | 14 KB | ||
| 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 | ||
| 1. What is NLP.mp4 | 75.7 MB | ||
| 1. What is NLP.srt | 7.7 KB | ||
| 1. What is NLP.vtt | 6.7 KB | ||
| 1. Where you go from here.html | 716.8 B | ||
| 10. Introduction to Classes and Objects.mp4 | 92.4 MB | ||
| 10. Introduction to Classes and Objects.srt | 9.4 KB | ||
| 10. Introduction to Classes and Objects.vtt | 8.2 KB | ||
| 10. Named Entity Recognition.mp4 | 56.1 MB | ||
| 10. Named Entity Recognition.srt | 6.8 KB | ||
| 10. Named Entity Recognition.vtt | 6 KB | ||
| 10. Training our classifier.mp4 | 30.7 MB | ||
| 10. Training our classifier.srt | 2.3 KB | ||
| 10. Training our classifier.vtt | 2 KB | ||
| 11. List Comprehension.mp4 | 165.5 MB | ||
| 11. List Comprehension.srt | 16.6 KB | ||
| 11. List Comprehension.vtt | 14.3 KB | ||
| 11. Testing Model performance.mp4 | 84 MB | ||
| 11. Testing Model performance.srt | 7.2 KB | ||
| 11. Testing Model performance.vtt | 6.2 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 | ||
| 12. Saving our Model.mp4 | 96.6 MB | ||
| 12. Saving our Model.srt | 7.8 KB | ||
| 12. Saving our Model.vtt | 6.8 KB | ||
| 12. Test Your Skills.html | 204.8 B | ||
| 13. Building the BOW Model Part 2.mp4 | 82.2 MB | ||
| 13. Building the BOW Model Part 2.srt | 6 KB | ||
| 13. Building the BOW Model Part 2.vtt | 5.3 KB | ||
| 13. Importing and using our Model.mp4 | 56.1 MB | ||
| 13. Importing and using our Model.srt | 5 KB | ||
| 13. Importing and using our Model.vtt | 4.3 KB | ||
| 14. Building the BOW Model Part 3.mp4 | 77 MB | ||
| 14. Building the BOW Model Part 3.srt | 5.7 KB | ||
| 14. Building the BOW Model Part 3.vtt | 5 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 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 | ||
| 2. Conditional Statements.mp4 | 63.8 MB | ||
| 2. Conditional Statements.srt | 7 KB | ||
| 2. Conditional Statements.vtt | 6.1 KB | ||
| 2. Fetching article data from the web.mp4 | 43.9 MB | ||
| 2. Fetching article data from the web.srt | 5.9 KB | ||
| 2. Fetching article data from the web.vtt | 5.1 KB | ||
| 2. Finding Patterns in Text Part 1.mp4 | 79.5 MB | ||
| 2. Finding Patterns in Text Part 1.srt | 10.9 KB | ||
| 2. Finding Patterns in Text Part 1.vtt | 9.5 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 | ||
| 2. Getting the data for Text Classification - Text.html | 819.2 B | ||
| 2. Importing the data.mp4 | 54.9 MB | ||
| 2. Importing the data.srt | 6.5 KB | ||
| 2. Importing the data.vtt | 5.6 KB | ||
| 2. Initializing Tokens.mp4 | 35.1 MB | ||
| 2. Initializing Tokens.srt | 5.3 KB | ||
| 2. Initializing Tokens.vtt | 4.6 KB | ||
| 2. Installing Anaconda Python - Text.html | 716.8 B | ||
| 2. Introduction to Pandas.mp4 | 251.6 MB | ||
| 2. Introduction to Pandas.srt | 28.6 KB | ||
| 2. Introduction to Pandas.vtt | 24.7 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 | ||
| 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.mp4 | 295.6 MB | ||
| 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 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 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 | ||
| 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 | ||
| 3. Client Authentication.mp4 | 46.7 MB | ||
| 3. Client Authentication.srt | 4.6 KB | ||
| 3. Client Authentication.vtt | 4 KB | ||
| 3. Finding Patterns in Text Part 2.mp4 | 81.5 MB | ||
| 3. Finding Patterns in Text Part 2.srt | 9.9 KB | ||
| 3. Finding Patterns in Text Part 2.vtt | 8.6 KB | ||
| 3. Getting the Course Resources - Text.html | 614.4 B | ||
| 3. How tokenization works - Text.html | 1.6 KB | ||
| 3. Importing the dataset.mp4 | 57.5 MB | ||
| 3. Importing the dataset.srt | 6.6 KB | ||
| 3. Importing the dataset.vtt | 5.8 KB | ||
| 3. Introduction to Loops.mp4 | 64.8 MB | ||
| 3. Introduction to Loops.srt | 9.8 KB | ||
| 3. Introduction to Loops.vtt | 8.6 KB | ||
| 3. Parsing the data using Beautiful Soup.mp4 | 94.3 MB | ||
| 3. Parsing the data using Beautiful Soup.srt | 9.5 KB | ||
| 3. Parsing the data using Beautiful Soup.vtt | 8.2 KB | ||
| 3. Preparing the data.mp4 | 38.5 MB | ||
| 3. Preparing the data.srt | 4.1 KB | ||
| 3. Preparing the data.vtt | 3.6 KB | ||
| 4. Fetching real time tweets.mp4 | 80.9 MB | ||
| 4. Fetching real time tweets.srt | 6.7 KB | ||
| 4. Fetching real time tweets.vtt | 5.9 KB | ||
| 4. How to take this course.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 | ||
| 4. Loop Control Statements.mp4 | 62 MB | ||
| 4. Loop Control Statements.srt | 9.4 KB | ||
| 4. Loop Control Statements.vtt | 8.2 KB | ||
| 4. Persisting the dataset.mp4 | 71.6 MB | ||
| 4. Persisting the dataset.srt | 6.5 KB | ||
| 4. Persisting the dataset.vtt | 5.7 KB | ||
| 4. Preprocessing the data.mp4 | 48.3 MB | ||
| 4. Preprocessing the data.srt | 4.1 KB | ||
| 4. Preprocessing the data.vtt | 3.6 KB | ||
| 4. Substituting Patterns in Text.mp4 | 54.2 MB | ||
| 4. Substituting Patterns in Text.srt | 8.1 KB | ||
| 4. Substituting Patterns in Text.vtt | 7 KB | ||
| 4. Training the Word2Vec Model.mp4 | 33.8 MB | ||
| 4. Training the Word2Vec Model.srt | 3.5 KB | ||
| 4. Training the Word2Vec Model.vtt | 3 KB | ||
| 5. Loading TF-IDF Model and Classifier.mp4 | 36 MB | ||
| 5. Loading TF-IDF Model and Classifier.srt | 2.5 KB | ||
| 5. Loading TF-IDF Model and Classifier.vtt | 2.2 KB | ||
| 5. Preprocessing the data.mp4 | 67.4 MB | ||
| 5. Preprocessing the data.srt | 6 KB | ||
| 5. Preprocessing the data.vtt | 5.2 KB | ||
| 5. Python Data Structures - Lists.mp4 | 129.2 MB | ||
| 5. Python Data Structures - Lists.srt | 16 KB | ||
| 5. Python Data Structures - Lists.vtt | 13.9 KB | ||
| 5. Shorthand Character Classes.mp4 | 182.4 MB | ||
| 5. Shorthand Character Classes.srt | 17.3 KB | ||
| 5. Shorthand Character Classes.vtt | 15 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 | ||
| 5. Testing Model Performance.mp4 | 54.5 MB | ||
| 5. Testing Model Performance.srt | 4.9 KB | ||
| 5. Testing Model Performance.vtt | 4.3 KB | ||
| 5. Tokenizing Article into sentences.mp4 | 50.7 MB | ||
| 5. Tokenizing Article into sentences.srt | 4.5 KB | ||
| 5. Tokenizing Article into sentences.vtt | 3.9 KB | ||
| 6. Building the histogram.mp4 | 58.6 MB | ||
| 6. Building the histogram.srt | 5.4 KB | ||
| 6. Building the histogram.vtt | 4.7 KB | ||
| 6. Character Ranges - Text.html | 1.2 KB | ||
| 6. Improving the Model.mp4 | 108.2 MB | ||
| 6. Improving the Model.srt | 7.8 KB | ||
| 6. Improving the Model.vtt | 6.7 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 | ||
| 6. Preprocessing the tweets.mp4 | 133.1 MB | ||
| 6. Preprocessing the tweets.srt | 7 KB | ||
| 6. Preprocessing the tweets.vtt | 6 KB | ||
| 6. Python Data Structures - Tuples.mp4 | 60.9 MB | ||
| 6. Python Data Structures - Tuples.srt | 7.1 KB | ||
| 6. Python Data Structures - Tuples.vtt | 6.1 KB | ||
| 6. Transforming data into BOW Model.mp4 | 114.7 MB | ||
| 6. Transforming data into BOW Model.srt | 9.7 KB | ||
| 6. Transforming data into BOW Model.vtt | 8.6 KB | ||
| 7. Calculating the sentence scores.mp4 | 99.8 MB | ||
| 7. Calculating the sentence scores.srt | 7.9 KB | ||
| 7. Calculating the sentence scores.vtt | 7 KB | ||
| 7. Exploring Pre-trained Models.mp4 | 50.4 MB | ||
| 7. Exploring Pre-trained Models.srt | 6.7 KB | ||
| 7. Exploring Pre-trained Models.vtt | 5.9 KB | ||
| 7. Predicting sentiments of tweets.mp4 | 38.1 MB | ||
| 7. Predicting sentiments of tweets.srt | 2.3 KB | ||
| 7. Predicting sentiments of tweets.vtt | 2 KB | ||
| 7. Preprocessing using Regex.mp4 | 71.6 MB | ||
| 7. Preprocessing using Regex.srt | 8 KB | ||
| 7. Preprocessing using Regex.vtt | 6.9 KB | ||
| 7. Python Data Structures - Dictionaries.mp4 | 125.1 MB | ||
| 7. Python Data Structures - Dictionaries.srt | 14.2 KB | ||
| 7. Python Data Structures - Dictionaries.vtt | 12.4 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 | ||
| 7. Transform BOW model into TF-IDF Model.mp4 | 47.4 MB | ||
| 7. Transform BOW model into TF-IDF Model.srt | 3.9 KB | ||
| 7. Transform BOW model into TF-IDF Model.vtt | 3.4 KB | ||
| 8. Console and File IO in Python.mp4 | 97 MB | ||
| 8. Console and File IO in Python.srt | 9.7 KB | ||
| 8. Console and File IO in Python.vtt | 8.4 KB | ||
| 8. Creating training and test set.mp4 | 71.8 MB | ||
| 8. Creating training and test set.srt | 5.7 KB | ||
| 8. Creating training and test set.vtt | 5 KB | ||
| 8. Getting the summary.mp4 | 76.9 MB | ||
| 8. Getting the summary.srt | 6 KB | ||
| 8. Getting the summary.vtt | 5.2 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 | ||
| 8. Plotting the results.mp4 | 102.7 MB | ||
| 8. Plotting the results.srt | 8.7 KB | ||
| 8. Plotting the results.vtt | 7.6 KB | ||
| 8. Test Your Skills.html | 204.8 B | ||
| 9. Introduction to Functions.mp4 | 76.8 MB | ||
| 9. Introduction to Functions.srt | 8.3 KB | ||
| 9. Introduction to Functions.vtt | 7.2 KB | ||
| 9. POS Tag Meanings.html | 3.3 KB | ||
| 9. Understanding Logistic Regression.mp4 | 201.6 MB | ||
| 9. Understanding Logistic Regression.srt | 20.4 KB | ||
| 9. Understanding Logistic Regression.vtt | 17.9 KB | ||
| [FTU Forum].url | 204.8 B | ||
| [FreeCoursesOnline.Me].url | 102.4 B | ||
| [FreeTutorials.Us].url | 102.4 B | ||
| ▲ 268 total files | |||
[UDEMY] HANDS ON NATURAL LANGUAGE PROCESSING (NLP) USING PYTHON [FTU]
Learn Natural Language Processing ( NLP ) & Text Mining by creating text classifier, article summarizer, and many more.
Best Seller
Created by Next Edge Coding
Last updated 7/2018
English
What Will I 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
For More Udemy Free Courses >>> http://www.freetutorials.us
For more Lynda and other Courses >>> https://www.freecoursesonline.me/
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