Unsupervised Machine Learning Hidden Markov Models in Python

1. 01 Introduction and Outline/001 Introduction and Outline Why would you want to use an HMM.mp46.78MB
2. 01 Introduction and Outline/002 Unsupervised or Supervised.mp45.27MB
3. 01 Introduction and Outline/003 Where to get the Code and Data.mp42.09MB
4. 01 Introduction and Outline/004 How to Succeed in this Course.mp48.78MB
5. 02 Markov Models/005 The Markov Property.mp48.31MB
6. 02 Markov Models/006 Markov Models.mp48.17MB
7. 02 Markov Models/007 The Math of Markov Chains.mp49.04MB
8. 03 Markov Models Example Problems and Applications/008 Example Problem Sick or Healthy.mp45.54MB
9. 03 Markov Models Example Problems and Applications/009 Example Problem Expected number of continuously sick days.mp44.63MB
10. 03 Markov Models Example Problems and Applications/010 Example application SEO and Bounce Rate Optimization.mp415.82MB
11. 03 Markov Models Example Problems and Applications/011 Example Application Build a 2nd-order language model and generate phrases.mp426.93MB
12. 03 Markov Models Example Problems and Applications/012 Example Application Googles PageRank algorithm.mp48.72MB
13. 04 Hidden Markov Models for Discrete Observations/013 From Markov Models to Hidden Markov Models.mp410.17MB
14. 04 Hidden Markov Models for Discrete Observations/014 HMMs are Doubly Embedded.mp43.14MB
15. 04 Hidden Markov Models for Discrete Observations/015 How can we choose the number of hidden states.mp47.34MB
16. 04 Hidden Markov Models for Discrete Observations/016 The Forward-Backward Algorithm.mp46.78MB
17. 04 Hidden Markov Models for Discrete Observations/017 Visual Intuition for the Forward Algorithm.mp46.03MB
18. 04 Hidden Markov Models for Discrete Observations/018 The Viterbi Algorithm.mp45.03MB
19. 04 Hidden Markov Models for Discrete Observations/019 Visual Intuition for the Viterbi Algorithm.mp45.73MB
20. 04 Hidden Markov Models for Discrete Observations/020 The Baum-Welch Algorithm.mp44.35MB
21. 04 Hidden Markov Models for Discrete Observations/021 Baum-Welch Explanation and Intuition.mp411.96MB
22. 04 Hidden Markov Models for Discrete Observations/022 Baum-Welch Updates for Multiple Observations.mp47.48MB
23. 04 Hidden Markov Models for Discrete Observations/023 Discrete HMM in Code.mp447.42MB
24. 04 Hidden Markov Models for Discrete Observations/024 The underflow problem and how to solve it.mp47.65MB
25. 04 Hidden Markov Models for Discrete Observations/025 Discrete HMM Updates in Code with Scaling.mp429.14MB
26. 04 Hidden Markov Models for Discrete Observations/026 Scaled Viterbi Algorithm in Log Space.mp49.23MB
27. 05 Discrete HMMs Using Deep Learning Libraries/027 Gradient Descent Tutorial.mp48.43MB
28. 05 Discrete HMMs Using Deep Learning Libraries/028 Theano Scan Tutorial.mp423.76MB
29. 05 Discrete HMMs Using Deep Learning Libraries/029 Discrete HMM in Theano.mp430.74MB
30. 05 Discrete HMMs Using Deep Learning Libraries/030 Improving our Gradient Descent-Based HMM.mp48MB
31. 05 Discrete HMMs Using Deep Learning Libraries/031 Tensorflow Scan Tutorial.mp423.07MB
32. 05 Discrete HMMs Using Deep Learning Libraries/032 Discrete HMM in Tensorflow.mp416.44MB
33. 06 HMMs for Continuous Observations/033 Gaussian Mixture Models with Hidden Markov Models.mp46.27MB
34. 06 HMMs for Continuous Observations/034 Generating Data from a Real-Valued HMM.mp414.94MB
35. 06 HMMs for Continuous Observations/035 Continuous-Observation HMM in Code part 1.mp446.69MB
36. 06 HMMs for Continuous Observations/036 Continuous-Observation HMM in Code part 2.mp415.28MB
37. 06 HMMs for Continuous Observations/037 Continuous HMM in Theano.mp445.41MB
38. 06 HMMs for Continuous Observations/038 Continuous HMM in Tensorflow.mp422.45MB
39. 07 HMMs for Classification/039 Generative vs. Discriminative Classifiers.mp44.12MB
40. 07 HMMs for Classification/040 HMM Classification on Poetry Data Robert Frost vs. Edgar Allan Poe.mp424.39MB
41. 08 Bonus Example Parts-of-Speech Tagging/041 Parts-of-Speech Tagging Concepts.mp48.51MB
42. 08 Bonus Example Parts-of-Speech Tagging/042 POS Tagging with an HMM.mp414.38MB
43. 09 Appendix/043 Review of Gaussian Mixture Models.mp44.99MB
44. 09 Appendix/044 Theano Tutorial.mp419.86MB
45. 09 Appendix/045 Tensorflow Tutorial.mp413.88MB
46. 09 Appendix/046 How to install Numpy Scipy Matplotlib Pandas IPython Theano and TensorFlow.mp443.92MB
47. 09 Appendix/047 How to Code by Yourself part 1.mp424.53MB
48. 09 Appendix/048 How to Code by Yourself part 2.mp414.8MB
49. 09 Appendix/049 BONUS Where to get Udemy coupons and FREE deep learning material.mp44.02MB