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Hands On Natural Language Processing (NLP) using Python
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Hands On Natural Language Processing (NLP) using Python (Size: 7.99 GB) (Files: 269)
Hands On Natural Language Processing (NLP) using Python
6. NLP Core
25. LSA in Python Part 1.mp4
1. Installing NLTK in Python.mp4
1. Installing NLTK in Python.srt
1. Installing NLTK in Python.vtt
2. Tokenizing Words and Sentences.mp4
2. Tokenizing Words and Sentences.srt
2. Tokenizing Words and Sentences.vtt
3. How tokenization works - Text.html
4. Introduction to Stemming and Lemmatization.mp4
4. Introduction to Stemming and Lemmatization.srt
4. Introduction to Stemming and Lemmatization.vtt
5. Stemming using NLTK.mp4
5. Stemming using NLTK.srt
5. Stemming using NLTK.vtt
6. Lemmatization using NLTK.mp4
6. Lemmatization using NLTK.srt
6. Lemmatization using NLTK.vtt
7. Stop word removal using NLTK.mp4
7. Stop word removal using NLTK.srt
7. Stop word removal using NLTK.vtt
8. Parts Of Speech Tagging.mp4
8. Parts Of Speech Tagging.srt
8. Parts Of Speech Tagging.vtt
9. POS Tag Meanings.html
10. Named Entity Recognition.mp4
10. Named Entity Recognition.srt
10. Named Entity Recognition.vtt
11. Text Modelling using Bag of Words Model.mp4
11. Text Modelling using Bag of Words Model.srt
11. Text Modelling using Bag of Words Model.vtt
12. Building the BOW Model Part 1.mp4
12. Building the BOW Model Part 1.srt
12. Building the BOW Model Part 1.vtt
13. Building the BOW Model Part 2.mp4
13. Building the BOW Model Part 2.srt
13. Building the BOW Model Part 2.vtt
14. Building the BOW Model Part 3.mp4
14. Building the BOW Model Part 3.srt
14. Building the BOW Model Part 3.vtt
15. Building the BOW Model Part 4.mp4
15. Building the BOW Model Part 4.srt
15. Building the BOW Model Part 4.vtt
16. Text Modelling using TF-IDF Model.mp4
16. Text Modelling using TF-IDF Model.srt
16. Text Modelling using TF-IDF Model.vtt
17. Building the TF-IDF Model Part 1.mp4
17. Building the TF-IDF Model Part 1.srt
17. Building the TF-IDF Model Part 1.vtt
18. Building the TF-IDF Model Part 2.mp4
18. Building the TF-IDF Model Part 2.srt
18. Building the TF-IDF Model Part 2.vtt
19. Building the TF-IDF Model Part 3.mp4
19. Building the TF-IDF Model Part 3.srt
19. Building the TF-IDF Model Part 3.vtt
20. Building the TF-IDF Model Part 4.mp4
20. Building the TF-IDF Model Part 4.srt
20. Building the TF-IDF Model Part 4.vtt
21. Understanding the N-Gram Model.mp4
21. Understanding the N-Gram Model.srt
21. Understanding the N-Gram Model.vtt
22. Building Character N-Gram Model.mp4
22. Building Character N-Gram Model.srt
22. Building Character N-Gram Model.vtt
23. Building Word N-Gram Model.mp4
23. Building Word N-Gram Model.srt
23. Building Word N-Gram Model.vtt
24. Understanding Latent Semantic Analysis.mp4
24. Understanding Latent Semantic Analysis.srt
24. Understanding Latent Semantic Analysis.vtt
25. LSA in Python Part 1.srt
25. LSA in Python Part 1.vtt
26. LSA in Python Part 2.mp4
26. LSA in Python Part 2.srt
26. LSA in Python Part 2.vtt
27. Word Synonyms and Antonyms using NLTK.mp4
27. Word Synonyms and Antonyms using NLTK.srt
27. Word Synonyms and Antonyms using NLTK.vtt
28. Word Negation Tracking in Python Part 1.mp4
28. Word Negation Tracking in Python Part 1.srt
28. Word Negation Tracking in Python Part 1.vtt
29. Word Negation Tracking in Python Part 2.mp4
29. Word Negation Tracking in Python Part 2.srt
29. Word Negation Tracking in Python Part 2.vtt
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1. Introduction to the Course
1. What is NLP.mp4
1. What is NLP.srt
1. What is NLP.vtt
2. Getting the Course Resources.mp4
2. Getting the Course Resources.srt
2. Getting the Course Resources.vtt
3. Getting the Course Resources - Text.html
2. Getting the required softwares
1. Installing Anaconda Python.mp4
1. Installing Anaconda Python.srt
1. Installing Anaconda Python.vtt
2. Installing Anaconda Python - Text.html
3. A tour of Spyder IDE.mp4
3. A tour of Spyder IDE.srt
3. A tour of Spyder IDE.vtt
4. How to take this course.html
3. Python Crash Course
1. Variables and Operations in Python.mp4
1. Variables and Operations in Python.srt
1. Variables and Operations in Python.vtt
2. Conditional Statements.mp4
2. Conditional Statements.srt
2. Conditional Statements.vtt
3. Introduction to Loops.mp4
3. Introduction to Loops.srt
3. Introduction to Loops.vtt
4. Loop Control Statements.mp4
4. Loop Control Statements.srt
4. Loop Control Statements.vtt
5. Python Data Structures - Lists.mp4
5. Python Data Structures - Lists.srt
5. Python Data Structures - Lists.vtt
6. Python Data Structures - Tuples.mp4
6. Python Data Structures - Tuples.srt
6. Python Data Structures - Tuples.vtt
7. Python Data Structures - Dictionaries.mp4
7. Python Data Structures - Dictionaries.srt
7. Python Data Structures - Dictionaries.vtt
8. Console and File IO in Python.mp4
8. Console and File IO in Python.srt
8. Console and File IO in Python.vtt
9. Introduction to Functions.mp4
9. Introduction to Functions.srt
9. Introduction to Functions.vtt
10. Introduction to Classes and Objects.mp4
10. Introduction to Classes and Objects.srt
10. Introduction to Classes and Objects.vtt
11. List Comprehension.mp4
11. List Comprehension.srt
11. List Comprehension.vtt
12. Test Your Skills.html
4. Regular Expressions
1. Introduction to Regular Expressions.mp4
1. Introduction to Regular Expressions.srt
1. Introduction to Regular Expressions.vtt
2. Finding Patterns in Text Part 1.mp4
2. Finding Patterns in Text Part 1.srt
2. Finding Patterns in Text Part 1.vtt
3. Finding Patterns in Text Part 2.mp4
3. Finding Patterns in Text Part 2.srt
3. Finding Patterns in Text Part 2.vtt
4. Substituting Patterns in Text.mp4
4. Substituting Patterns in Text.srt
4. Substituting Patterns in Text.vtt
5. Shorthand Character Classes.mp4
5. Shorthand Character Classes.srt
5. Shorthand Character Classes.vtt
6. Character Ranges - Text.html
7. Preprocessing using Regex.mp4
7. Preprocessing using Regex.srt
7. Preprocessing using Regex.vtt
8. Test Your Skills.html
5. Numpy and Pandas
1. Introduction to Numpy.mp4
1. Introduction to Numpy.srt
1. Introduction to Numpy.vtt
2. Introduction to Pandas.mp4
2. Introduction to Pandas.srt
2. Introduction to Pandas.vtt
7. Project 1 - Text Classification
1. Getting the data for Text Classification.mp4
1. Getting the data for Text Classification.srt
1. Getting the data for Text Classification.vtt
2. Getting the data for Text Classification - Text.html
3. Importing the dataset.mp4
3. Importing the dataset.srt
3. Importing the dataset.vtt
4. Persisting the dataset.mp4
4. Persisting the dataset.srt
4. Persisting the dataset.vtt
5. Preprocessing the data.mp4
5. Preprocessing the data.srt
5. Preprocessing the data.vtt
6. Transforming data into BOW Model.mp4
6. Transforming data into BOW Model.srt
6. Transforming data into BOW Model.vtt
7. Transform BOW model into TF-IDF Model.mp4
7. Transform BOW model into TF-IDF Model.srt
7. Transform BOW model into TF-IDF Model.vtt
8. Creating training and test set.mp4
8. Creating training and test set.srt
8. Creating training and test set.vtt
9. Understanding Logistic Regression.mp4
9. Understanding Logistic Regression.srt
9. Understanding Logistic Regression.vtt
10. Training our classifier.mp4
10. Training our classifier.srt
10. Training our classifier.vtt
11. Testing Model performance.mp4
11. Testing Model performance.srt
11. Testing Model performance.vtt
12. Saving our Model.mp4
12. Saving our Model.srt
12. Saving our Model.vtt
13. Importing and using our Model.mp4
13. Importing and using our Model.srt
13. Importing and using our Model.vtt
8. Project 2 - Twitter Sentiment Analysis
1. Setting up Twitter Application.mp4
1. Setting up Twitter Application.srt
1. Setting up Twitter Application.vtt
2. Initializing Tokens.mp4
2. Initializing Tokens.srt
2. Initializing Tokens.vtt
3. Client Authentication.mp4
3. Client Authentication.srt
3. Client Authentication.vtt
4. Fetching real time tweets.mp4
4. Fetching real time tweets.srt
4. Fetching real time tweets.vtt
5. Loading TF-IDF Model and Classifier.mp4
5. Loading TF-IDF Model and Classifier.srt
5. Loading TF-IDF Model and Classifier.vtt
6. Preprocessing the tweets.mp4
6. Preprocessing the tweets.srt
6. Preprocessing the tweets.vtt
7. Predicting sentiments of tweets.mp4
7. Predicting sentiments of tweets.srt
7. Predicting sentiments of tweets.vtt
8. Plotting the results.mp4
8. Plotting the results.srt
8. Plotting the results.vtt
9. Project 3 - Text Summarization
1. Understanding Text Summarization.mp4
1. Understanding Text Summarization.srt
1. Understanding Text Summarization.vtt
2. Fetching article data from the web.mp4
2. Fetching article data from the web.srt
2. Fetching article data from the web.vtt
3. Parsing the data using Beautiful Soup.mp4
3. Parsing the data using Beautiful Soup.srt
3. Parsing the data using Beautiful Soup.vtt
4. Preprocessing the data.mp4
4. Preprocessing the data.srt
4. Preprocessing the data.vtt
5. Tokenizing Article into sentences.mp4
5. Tokenizing Article into sentences.srt
5. Tokenizing Article into sentences.vtt
6. Building the histogram.mp4
6. Building the histogram.srt
6. Building the histogram.vtt
7. Calculating the sentence scores.mp4
7. Calculating the sentence scores.srt
7. Calculating the sentence scores.vtt
8. Getting the summary.mp4
8. Getting the summary.srt
8. Getting the summary.vtt
10. Word2Vec Analysis
1. Understanding Word Vectors.mp4
1. Understanding Word Vectors.srt
1. Understanding Word Vectors.vtt
2. Importing the data.mp4
2. Importing the data.srt
2. Importing the data.vtt
3. Preparing the data.mp4
3. Preparing the data.srt
3. Preparing the data.vtt
4. Training the Word2Vec Model.mp4
4. Training the Word2Vec Model.srt
4. Training the Word2Vec Model.vtt
5. Testing Model Performance.mp4
5. Testing Model Performance.srt
5. Testing Model Performance.vtt
6. Improving the Model.mp4
6. Improving the Model.srt
6. Improving the Model.vtt
7. Exploring Pre-trained Models.mp4
7. Exploring Pre-trained Models.srt
7. Exploring Pre-trained Models.vtt
11. Conclusion
1. Where you go from here.html
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Course Downloaded from coursedrive.org.txt
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