UdemyCourseDownloader Mining Data from Text

1. 1.Course Overview/01.Course Overview.mp43.15MB
2. 2.Modeling Text Using Natural Language Processing/02.Module Overview.mp41.94MB
3. 2.Modeling Text Using Natural Language Processing/03.Prerequisites and Course Outline .mp41.45MB
4. 2.Modeling Text Using Natural Language Processing/04.Mining Data from Text.mp42.72MB
5. 2.Modeling Text Using Natural Language Processing/05.Numeric Representations of Text - One Hot Encoding.mp47.19MB
6. 2.Modeling Text Using Natural Language Processing/06.Numeric Representations of Text - Frequency Based Encodings.mp46.96MB
7. 2.Modeling Text Using Natural Language Processing/07.Numeric Representations of Text - Prediction Based Embeddings.mp44.82MB
8. 2.Modeling Text Using Natural Language Processing/08.Feature Hashing.mp45.02MB
9. 2.Modeling Text Using Natural Language Processing/09.Bag of Words - Bag of N Grams.mp43.52MB
10. 2.Modeling Text Using Natural Language Processing/10.Install and Setup.mp44.87MB
11. 2.Modeling Text Using Natural Language Processing/11.Frequency Based Representation Using Bag of Words and Bag of N Grams Model.mp413.97MB
12. 2.Modeling Text Using Natural Language Processing/12.Representing Documents Using TFIDF Scores and Feature Hashes.mp412.61MB
13. 2.Modeling Text Using Natural Language Processing/13.Module Summary.mp42.19MB
14. 3.Building Classification Models Using Text Data/14.Module Overview.mp41.78MB
15. 3.Building Classification Models Using Text Data/15.Naive Bayes Classifier.mp45.9MB
16. 3.Building Classification Models Using Text Data/16.Sentiment Analysis Using the Naive Bayes Classifier.mp414.14MB
17. 3.Building Classification Models Using Text Data/17.scikit-learn Pipelines to Build Features .mp410.4MB
18. 3.Building Classification Models Using Text Data/18.Multiclass Classification.mp49.91MB
19. 3.Building Classification Models Using Text Data/19.Module Summary.mp41.59MB
20. 4.Understanding Topic Modeling/20.Module Overview.mp42.32MB
21. 4.Understanding Topic Modeling/21.Topic Modeling.mp410.29MB
22. 4.Understanding Topic Modeling/22.Topic Modeling Algorithms.mp49.39MB
23. 4.Understanding Topic Modeling/23.Module Summary.mp41.95MB
24. 5.Implementing Topic Modeling/24.Module Overview.mp41.87MB
25. 5.Implementing Topic Modeling/25.Latent Dirichlet Allocation - Topic Modeling with the Newspaper Headlines Dataset.mp412.53MB
26. 5.Implementing Topic Modeling/26.Visualizing Topic Assignments Using Manifold Learning to Reduce Dimensions.mp411.65MB
27. 5.Implementing Topic Modeling/27.Latent Dirichlet Allocation - Topic Modeling with the DBPedia Dataset.mp415.41MB
28. 5.Implementing Topic Modeling/28.Visualizing Topics Using Manifold Learning to Reduce Dimensions .mp418.18MB
29. 5.Implementing Topic Modeling/29.Interactive Topic Model Visualization Using PyLDAVis.mp47.01MB
30. 5.Implementing Topic Modeling/30.Non-negative Matrix Factorization - Topic Modeling with the DBPedia Dataset.mp49.77MB
31. 5.Implementing Topic Modeling/31.Interactive Topic Visualization Using Bokeh.mp410.27MB
32. 5.Implementing Topic Modeling/32.Latent Semantic Indexing - Preprocessing Text.mp413.32MB
33. 5.Implementing Topic Modeling/33.Concept Modeling Using LSI.mp410.78MB
34. 5.Implementing Topic Modeling/34.Module Summary.mp41.8MB
35. 6.Understanding and Implementing Keyword Extraction/35.Module Overview.mp41.88MB
36. 6.Understanding and Implementing Keyword Extraction/36.Understanding RAKE for Keyword Extraction.mp46.2MB
37. 6.Understanding and Implementing Keyword Extraction/37.Keyword Extraction Using RAKE.mp415.22MB
38. 6.Understanding and Implementing Keyword Extraction/38.Summary and Further Study.mp42.03MB