GigaCourse com Udemy - Unsupervised Machine Learning Hidden Markov Models in Python

1. 1. Introduction and Outline/1. Introduction and Outline Why would you want to use an HMM.mp46.78MB
2. 1. Introduction and Outline/2. Unsupervised or Supervised.mp45.27MB
3. 1. Introduction and Outline/3. Where to get the Code and Data.mp42.09MB
4. 1. Introduction and Outline/4. How to Succeed in this Course.mp43.3MB
5. 10. Appendix/1. What is the Appendix.mp45.45MB
6. 10. Appendix/10. What order should I take your courses in (part 1).mp429.33MB
7. 10. Appendix/11. What order should I take your courses in (part 2).mp437.63MB
8. 10. Appendix/12. BONUS Where to get Udemy coupons and FREE deep learning material.mp44.03MB
9. 10. Appendix/2. Windows-Focused Environment Setup 2018.mp4186.33MB
10. 10. Appendix/3. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp443.92MB
11. 10. Appendix/4. How to Code by Yourself (part 1).mp424.54MB
12. 10. Appendix/5. How to Code by Yourself (part 2).mp414.81MB
13. 10. Appendix/6. How to Succeed in this Course (Long Version).mp418.32MB
14. 10. Appendix/7. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp438.96MB
15. 10. Appendix/8. Proof that using Jupyter Notebook is the same as not using it.mp478.28MB
16. 10. Appendix/9. Python 2 vs Python 3.mp47.84MB
17. 2. Markov Models/1. The Markov Property.mp48.31MB
18. 2. Markov Models/2. Markov Models.mp48.17MB
19. 2. Markov Models/3. The Math of Markov Chains.mp49.04MB
20. 3. Markov Models Example Problems and Applications/1. Example Problem Sick or Healthy.mp45.54MB
21. 3. Markov Models Example Problems and Applications/2. Example Problem Expected number of continuously sick days.mp44.63MB
22. 3. Markov Models Example Problems and Applications/3. Example application SEO and Bounce Rate Optimization.mp415.83MB
23. 3. Markov Models Example Problems and Applications/4. Example Application Build a 2nd-order language model and generate phrases.mp426.93MB
24. 3. Markov Models Example Problems and Applications/5. Example Application Google’s PageRank algorithm.mp48.72MB
25. 4. Hidden Markov Models for Discrete Observations/1. From Markov Models to Hidden Markov Models.mp410.17MB
26. 4. Hidden Markov Models for Discrete Observations/10. Baum-Welch Updates for Multiple Observations.mp47.48MB
27. 4. Hidden Markov Models for Discrete Observations/11. Discrete HMM in Code.mp447.43MB
28. 4. Hidden Markov Models for Discrete Observations/12. The underflow problem and how to solve it.mp47.65MB
29. 4. Hidden Markov Models for Discrete Observations/13. Discrete HMM Updates in Code with Scaling.mp429.14MB
30. 4. Hidden Markov Models for Discrete Observations/14. Scaled Viterbi Algorithm in Log Space.mp49.23MB
31. 4. Hidden Markov Models for Discrete Observations/2. HMMs are Doubly Embedded.mp41.54MB
32. 4. Hidden Markov Models for Discrete Observations/3. How can we choose the number of hidden states.mp47.35MB
33. 4. Hidden Markov Models for Discrete Observations/4. The Forward-Backward Algorithm.mp422.44MB
34. 4. Hidden Markov Models for Discrete Observations/5. Visual Intuition for the Forward Algorithm.mp46.03MB
35. 4. Hidden Markov Models for Discrete Observations/6. The Viterbi Algorithm.mp45.04MB
36. 4. Hidden Markov Models for Discrete Observations/7. Visual Intuition for the Viterbi Algorithm.mp415.68MB
37. 4. Hidden Markov Models for Discrete Observations/8. The Baum-Welch Algorithm.mp44.35MB
38. 4. Hidden Markov Models for Discrete Observations/9. Baum-Welch Explanation and Intuition.mp411.97MB
39. 5. Discrete HMMs Using Deep Learning Libraries/1. Gradient Descent Tutorial.mp422.81MB
40. 5. Discrete HMMs Using Deep Learning Libraries/2. Theano Scan Tutorial.mp423.76MB
41. 5. Discrete HMMs Using Deep Learning Libraries/3. Discrete HMM in Theano.mp430.74MB
42. 5. Discrete HMMs Using Deep Learning Libraries/4. Improving our Gradient Descent-Based HMM.mp425.95MB
43. 5. Discrete HMMs Using Deep Learning Libraries/5. Tensorflow Scan Tutorial.mp423.07MB
44. 5. Discrete HMMs Using Deep Learning Libraries/6. Discrete HMM in Tensorflow.mp416.44MB
45. 6. HMMs for Continuous Observations/1. Gaussian Mixture Models with Hidden Markov Models.mp416.46MB
46. 6. HMMs for Continuous Observations/2. Generating Data from a Real-Valued HMM.mp414.95MB
47. 6. HMMs for Continuous Observations/3. Continuous-Observation HMM in Code (part 1).mp446.69MB
48. 6. HMMs for Continuous Observations/4. Continuous-Observation HMM in Code (part 2).mp415.29MB
49. 6. HMMs for Continuous Observations/5. Continuous HMM in Theano.mp445.41MB
50. 6. HMMs for Continuous Observations/6. Continuous HMM in Tensorflow.mp422.46MB
51. 7. HMMs for Classification/1. Generative vs. Discriminative Classifiers.mp44.12MB
52. 7. HMMs for Classification/2. HMM Classification on Poetry Data (Robert Frost vs. Edgar Allan Poe).mp424.39MB
53. 8. Bonus Example Parts-of-Speech Tagging/1. Parts-of-Speech Tagging Concepts.mp48.51MB
54. 8. Bonus Example Parts-of-Speech Tagging/2. POS Tagging with an HMM.mp414.39MB
55. 9. Basics Review/1. (Review) Gaussian Mixture Models.mp44.99MB
56. 9. Basics Review/2. (Review) Theano Tutorial.mp419.86MB
57. 9. Basics Review/3. (Review) Tensorflow Tutorial.mp413.89MB