FreeCourseSite com Udemy - Data Science Natural Language Processing NLP in Python

1. 1. Natural Language Processing - What is it used for/1. Introduction and Outline.mp42.51MB
2. 1. Natural Language Processing - What is it used for/2. NLP Applications.mp45.72MB
3. 1. Natural Language Processing - What is it used for/3. Why is NLP hard.mp47.13MB
4. 1. Natural Language Processing - What is it used for/4. The Central Message of this Course.mp43.15MB
5. 10. Appendix/1. What is the Appendix.mp45.45MB
6. 10. Appendix/10. What order should I take your courses in (part 1).mp429.32MB
7. 10. Appendix/11. What order should I take your courses in (part 2).mp437.62MB
8. 10. Appendix/2. Windows-Focused Environment Setup 2018.mp4186.47MB
9. 10. Appendix/3. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp443.92MB
10. 10. Appendix/4. How to Code by Yourself (part 1).mp424.53MB
11. 10. Appendix/5. How to Code by Yourself (part 2).mp414.81MB
12. 10. Appendix/6. How to Succeed in this Course (Long Version).mp412.99MB
13. 10. Appendix/7. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp438.96MB
14. 10. Appendix/8. Proof that using Jupyter Notebook is the same as not using it.mp478.28MB
15. 10. Appendix/9. Python 2 vs Python 3.mp47.83MB
16. 2. Course Preparation/1. How to Succeed in this Course.mp43.3MB
17. 2. Course Preparation/2. Where to get the code and data.mp44.43MB
18. 2. Course Preparation/3. Do you need a review of machine learning.mp413.39MB
19. 3. Build your own spam detector/1. Build your own spam detector - description of data.mp41.9MB
20. 3. Build your own spam detector/10. SMS Spam in Code.mp413.92MB
21. 3. Build your own spam detector/2. Build your own spam detector using Naive Bayes and AdaBoost - the code.mp46.54MB
22. 3. Build your own spam detector/3. Key Takeaway from Spam Detection Exercise.mp430.59MB
23. 3. Build your own spam detector/4. Naive Bayes Concepts.mp439.65MB
24. 3. Build your own spam detector/5. AdaBoost Concepts.mp426.75MB
25. 3. Build your own spam detector/6. Other types of features.mp41.42MB
26. 3. Build your own spam detector/7. Spam Detection FAQ (Remedial #1).mp410.67MB
27. 3. Build your own spam detector/8. What is a Vector (Remedial #2).mp49.07MB
28. 3. Build your own spam detector/9. SMS Spam Example.mp45.71MB
29. 4. Build your own sentiment analyzer/1. Description of Sentiment Analyzer.mp45.06MB
30. 4. Build your own sentiment analyzer/2. Logistic Regression Review.mp412.2MB
31. 4. Build your own sentiment analyzer/3. Preprocessing Tokenization.mp47.73MB
32. 4. Build your own sentiment analyzer/4. Preprocessing Tokens to Vectors.mp410.55MB
33. 4. Build your own sentiment analyzer/5. Sentiment Analysis in Python using Logistic Regression.mp443.54MB
34. 4. Build your own sentiment analyzer/6. Sentiment Analysis Extension.mp45.16MB
35. 4. Build your own sentiment analyzer/7. How to Improve Sentiment Analysis & FAQ.mp477.73MB
36. 5. NLTK Exploration/1. NLTK Exploration POS Tagging.mp42.03MB
37. 5. NLTK Exploration/2. NLTK Exploration Stemming and Lemmatization.mp43.66MB
38. 5. NLTK Exploration/3. NLTK Exploration Named Entity Recognition.mp46.66MB
39. 5. NLTK Exploration/4. Want more NLTK.mp48.45MB
40. 6. Latent Semantic Analysis/1. Latent Semantic Analysis - What does it do.mp43.92MB
41. 6. Latent Semantic Analysis/2. SVD - The underlying math behind LSA.mp478.21MB
42. 6. Latent Semantic Analysis/3. Latent Semantic Analysis in Python.mp425.44MB
43. 6. Latent Semantic Analysis/4. What is Latent Semantic Analysis Used For.mp416.88MB
44. 6. Latent Semantic Analysis/5. Extending LSA.mp410.91MB
45. 7. Write your own article spinner/1. Article Spinning Introduction and Markov Models.mp44.66MB
46. 7. Write your own article spinner/2. More about Language Models.mp436.63MB
47. 7. Write your own article spinner/3. Trigram Model.mp43.85MB
48. 7. Write your own article spinner/4. Precode Exercises.mp419.77MB
49. 7. Write your own article spinner/5. Writing an article spinner in Python.mp425.95MB
50. 7. Write your own article spinner/6. Article Spinner Extension Exercises.mp423.68MB
51. 8. How to learn more about NLP/1. What we didn't talk about.mp44.32MB
52. 9. Machine Learning Basics Review/1. (Review) Machine Learning Section Introduction.mp444.86MB
53. 9. Machine Learning Basics Review/10. (Review) Machine Learning and Deep Learning Future Topics.mp440.86MB
54. 9. Machine Learning Basics Review/11. (Review) Section Summary.mp424.83MB
55. 9. Machine Learning Basics Review/2. (Review) What is Classification.mp470.67MB
56. 9. Machine Learning Basics Review/3. (Review) Classification in Code.mp4139.48MB
57. 9. Machine Learning Basics Review/4. (Review) What is Regression.mp449.56MB
58. 9. Machine Learning Basics Review/5. (Review) Regression in Code.mp469.37MB
59. 9. Machine Learning Basics Review/6. (Review) What is a Feature Vector.mp437.99MB
60. 9. Machine Learning Basics Review/7. (Review) Machine Learning is Nothing but Geometry.mp422.74MB
61. 9. Machine Learning Basics Review/8. (Review) All Data is the Same.mp424.8MB
62. 9. Machine Learning Basics Review/9. (Review) Comparing Different Machine Learning Models.mp453.55MB