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Data Science: Natural Language Processing (NLP) in Python
Natural Language Processing - What is it used for?
Introduction and Outline (7:48)
Special Offer! Get the VIP version of this course (1:14)
Why Learn NLP? (5:59)
The Central Message of this Course (8:12)
Course Preparation
How to Succeed in this Course (5:51)
Where to get the code (5:01)
Build your own spam detector
Build your own spam detector - description of data (2:08)
Build your own spam detector using Naive Bayes and AdaBoost - the code (5:14)
Other types of features (1:30)
Spam Detection FAQ (Remedial #1) (8:45)
What is a Vector? (Remedial #2) (6:04)
SMS Spam Example (6:23)
SMS Spam in Code (10:43)
Build your own sentiment analyzer
Description of Sentiment Analyzer (3:12)
Logistic Regression Review (7:32)
Preprocessing: Tokenization (4:48)
Preprocessing: Tokens to Vectors (6:20)
Sentiment Analysis in Python (19:48)
Sentiment Analysis Extension (6:01)
How to Improve Sentiment Analysis & FAQ (12:19)
NLTK Exploration
NLTK Exploration: POS Tagging (2:00)
NLTK Exploration: Stemming and Lemmatization (2:06)
NLTK Exploration: Named Entity Recognition (3:13)
Latent Semantic Analysis
Latent Semantic Analysis - What does it do? (2:30)
PCA and SVD - The underlying math behind LSA (7:59)
Latent Semantic Analysis in Python (10:08)
What is Latent Semantic Analysis Used For? (9:40)
Extending LSA (6:16)
Write your own article spinner
Article Spinning Introduction (2:43)
Trigram Model (2:12)
Writing an article spinner in Python (11:33)
How to learn more about NLP
What we didn't talk about (2:45)
Appendix
What order should I take your courses in? (part 1) (11:18)
What order should I take your courses in? (part 2) (16:07)
How to Code by Yourself (part 1) (15:54)
How to Code by Yourself (part 2) (9:23)
How to Succeed in this Course (Long Version) (10:24)
Python 2 vs Python 3 (4:38)
BONUS: Where to get discount coupons and FREE deep learning material (5:31)
Introduction and Outline
Complete and Continue