589689.xyz

[] Udemy - Unsupervised Machine Learning Hidden Markov Models in Python

  • 收录时间:2020-06-29 00:42:55
  • 文件大小:1GB
  • 下载次数:40
  • 最近下载:2021-01-15 16:09:12
  • 磁力链接:
立即下载 复制链接

文件列表

  1. 10. Appendix/2. Windows-Focused Environment Setup 2018.mp4 186MB
  2. 10. Appendix/8. Proof that using Jupyter Notebook is the same as not using it.mp4 78MB
  3. 4. Hidden Markov Models for Discrete Observations/11. Discrete HMM in Code.mp4 47MB
  4. 6. HMMs for Continuous Observations/3. Continuous-Observation HMM in Code (part 1).mp4 47MB
  5. 6. HMMs for Continuous Observations/5. Continuous HMM in Theano.mp4 45MB
  6. 10. Appendix/3. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 44MB
  7. 10. Appendix/7. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 39MB
  8. 10. Appendix/11. What order should I take your courses in (part 2).mp4 38MB
  9. 5. Discrete HMMs Using Deep Learning Libraries/3. Discrete HMM in Theano.mp4 31MB
  10. 10. Appendix/10. What order should I take your courses in (part 1).mp4 29MB
  11. 4. Hidden Markov Models for Discrete Observations/13. Discrete HMM Updates in Code with Scaling.mp4 29MB
  12. 3. Markov Models Example Problems and Applications/4. Example Application Build a 2nd-order language model and generate phrases.mp4 27MB
  13. 5. Discrete HMMs Using Deep Learning Libraries/4. Improving our Gradient Descent-Based HMM.mp4 26MB
  14. 10. Appendix/4. How to Code by Yourself (part 1).mp4 25MB
  15. 7. HMMs for Classification/2. HMM Classification on Poetry Data (Robert Frost vs. Edgar Allan Poe).mp4 24MB
  16. 5. Discrete HMMs Using Deep Learning Libraries/2. Theano Scan Tutorial.mp4 24MB
  17. 5. Discrete HMMs Using Deep Learning Libraries/5. Tensorflow Scan Tutorial.mp4 23MB
  18. 5. Discrete HMMs Using Deep Learning Libraries/1. Gradient Descent Tutorial.mp4 23MB
  19. 6. HMMs for Continuous Observations/6. Continuous HMM in Tensorflow.mp4 22MB
  20. 4. Hidden Markov Models for Discrete Observations/4. The Forward-Backward Algorithm.mp4 22MB
  21. 9. Basics Review/2. (Review) Theano Tutorial.mp4 20MB
  22. 10. Appendix/6. How to Succeed in this Course (Long Version).mp4 18MB
  23. 6. HMMs for Continuous Observations/1. Gaussian Mixture Models with Hidden Markov Models.mp4 16MB
  24. 5. Discrete HMMs Using Deep Learning Libraries/6. Discrete HMM in Tensorflow.mp4 16MB
  25. 3. Markov Models Example Problems and Applications/3. Example application SEO and Bounce Rate Optimization.mp4 16MB
  26. 4. Hidden Markov Models for Discrete Observations/7. Visual Intuition for the Viterbi Algorithm.mp4 16MB
  27. 6. HMMs for Continuous Observations/4. Continuous-Observation HMM in Code (part 2).mp4 15MB
  28. 6. HMMs for Continuous Observations/2. Generating Data from a Real-Valued HMM.mp4 15MB
  29. 10. Appendix/5. How to Code by Yourself (part 2).mp4 15MB
  30. 8. Bonus Example Parts-of-Speech Tagging/2. POS Tagging with an HMM.mp4 14MB
  31. 9. Basics Review/3. (Review) Tensorflow Tutorial.mp4 14MB
  32. 4. Hidden Markov Models for Discrete Observations/9. Baum-Welch Explanation and Intuition.mp4 12MB
  33. 4. Hidden Markov Models for Discrete Observations/1. From Markov Models to Hidden Markov Models.mp4 10MB
  34. 4. Hidden Markov Models for Discrete Observations/14. Scaled Viterbi Algorithm in Log Space.mp4 9MB
  35. 2. Markov Models/3. The Math of Markov Chains.mp4 9MB
  36. 3. Markov Models Example Problems and Applications/5. Example Application Google’s PageRank algorithm.mp4 9MB
  37. 8. Bonus Example Parts-of-Speech Tagging/1. Parts-of-Speech Tagging Concepts.mp4 9MB
  38. 2. Markov Models/1. The Markov Property.mp4 8MB
  39. 2. Markov Models/2. Markov Models.mp4 8MB
  40. 10. Appendix/9. Python 2 vs Python 3.mp4 8MB
  41. 4. Hidden Markov Models for Discrete Observations/12. The underflow problem and how to solve it.mp4 8MB
  42. 4. Hidden Markov Models for Discrete Observations/10. Baum-Welch Updates for Multiple Observations.mp4 7MB
  43. 4. Hidden Markov Models for Discrete Observations/3. How can we choose the number of hidden states.mp4 7MB
  44. 1. Introduction and Outline/1. Introduction and Outline Why would you want to use an HMM.mp4 7MB
  45. 4. Hidden Markov Models for Discrete Observations/5. Visual Intuition for the Forward Algorithm.mp4 6MB
  46. 3. Markov Models Example Problems and Applications/1. Example Problem Sick or Healthy.mp4 6MB
  47. 10. Appendix/1. What is the Appendix.mp4 5MB
  48. 1. Introduction and Outline/2. Unsupervised or Supervised.mp4 5MB
  49. 4. Hidden Markov Models for Discrete Observations/6. The Viterbi Algorithm.mp4 5MB
  50. 9. Basics Review/1. (Review) Gaussian Mixture Models.mp4 5MB
  51. 3. Markov Models Example Problems and Applications/2. Example Problem Expected number of continuously sick days.mp4 5MB
  52. 4. Hidden Markov Models for Discrete Observations/8. The Baum-Welch Algorithm.mp4 4MB
  53. 7. HMMs for Classification/1. Generative vs. Discriminative Classifiers.mp4 4MB
  54. 10. Appendix/12. BONUS Where to get Udemy coupons and FREE deep learning material.mp4 4MB
  55. 1. Introduction and Outline/4. How to Succeed in this Course.mp4 3MB
  56. 1. Introduction and Outline/3. Where to get the Code and Data.mp4 2MB
  57. 4. Hidden Markov Models for Discrete Observations/2. HMMs are Doubly Embedded.mp4 2MB
  58. 10. Appendix/7. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.vtt 30KB
  59. 10. Appendix/11. What order should I take your courses in (part 2).vtt 22KB
  60. 10. Appendix/4. How to Code by Yourself (part 1).vtt 21KB
  61. 10. Appendix/2. Windows-Focused Environment Setup 2018.vtt 19KB
  62. 10. Appendix/10. What order should I take your courses in (part 1).vtt 15KB
  63. 5. Discrete HMMs Using Deep Learning Libraries/5. Tensorflow Scan Tutorial.vtt 14KB
  64. 10. Appendix/6. How to Succeed in this Course (Long Version).vtt 14KB
  65. 4. Hidden Markov Models for Discrete Observations/11. Discrete HMM in Code.vtt 13KB
  66. 10. Appendix/3. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.vtt 13KB
  67. 10. Appendix/8. Proof that using Jupyter Notebook is the same as not using it.vtt 13KB
  68. 10. Appendix/5. How to Code by Yourself (part 2).vtt 12KB
  69. 3. Markov Models Example Problems and Applications/4. Example Application Build a 2nd-order language model and generate phrases.vtt 12KB
  70. 6. HMMs for Continuous Observations/3. Continuous-Observation HMM in Code (part 1).vtt 11KB
  71. 5. Discrete HMMs Using Deep Learning Libraries/2. Theano Scan Tutorial.vtt 11KB
  72. 6. HMMs for Continuous Observations/5. Continuous HMM in Theano.vtt 10KB
  73. 6. HMMs for Continuous Observations/6. Continuous HMM in Tensorflow.vtt 10KB
  74. 3. Markov Models Example Problems and Applications/3. Example application SEO and Bounce Rate Optimization.vtt 9KB
  75. 5. Discrete HMMs Using Deep Learning Libraries/6. Discrete HMM in Tensorflow.vtt 8KB
  76. 4. Hidden Markov Models for Discrete Observations/9. Baum-Welch Explanation and Intuition.vtt 8KB
  77. 4. Hidden Markov Models for Discrete Observations/1. From Markov Models to Hidden Markov Models.vtt 8KB
  78. 4. Hidden Markov Models for Discrete Observations/13. Discrete HMM Updates in Code with Scaling.vtt 8KB
  79. 7. HMMs for Classification/2. HMM Classification on Poetry Data (Robert Frost vs. Edgar Allan Poe).vtt 8KB
  80. 5. Discrete HMMs Using Deep Learning Libraries/3. Discrete HMM in Theano.vtt 7KB
  81. 9. Basics Review/2. (Review) Theano Tutorial.vtt 7KB
  82. 2. Markov Models/3. The Math of Markov Chains.vtt 7KB
  83. 3. Markov Models Example Problems and Applications/5. Example Application Google’s PageRank algorithm.vtt 7KB
  84. 8. Bonus Example Parts-of-Speech Tagging/1. Parts-of-Speech Tagging Concepts.vtt 6KB
  85. 2. Markov Models/1. The Markov Property.vtt 6KB
  86. 4. Hidden Markov Models for Discrete Observations/12. The underflow problem and how to solve it.vtt 6KB
  87. 2. Markov Models/2. Markov Models.vtt 6KB
  88. 5. Discrete HMMs Using Deep Learning Libraries/4. Improving our Gradient Descent-Based HMM.vtt 6KB
  89. 10. Appendix/9. Python 2 vs Python 3.vtt 6KB
  90. 9. Basics Review/3. (Review) Tensorflow Tutorial.vtt 6KB
  91. 4. Hidden Markov Models for Discrete Observations/10. Baum-Welch Updates for Multiple Observations.vtt 6KB
  92. 4. Hidden Markov Models for Discrete Observations/3. How can we choose the number of hidden states.vtt 6KB
  93. 1. Introduction and Outline/1. Introduction and Outline Why would you want to use an HMM.vtt 5KB
  94. 4. Hidden Markov Models for Discrete Observations/4. The Forward-Backward Algorithm.vtt 5KB
  95. 5. Discrete HMMs Using Deep Learning Libraries/1. Gradient Descent Tutorial.vtt 5KB
  96. 6. HMMs for Continuous Observations/1. Gaussian Mixture Models with Hidden Markov Models.vtt 5KB
  97. 8. Bonus Example Parts-of-Speech Tagging/2. POS Tagging with an HMM.vtt 5KB
  98. 4. Hidden Markov Models for Discrete Observations/5. Visual Intuition for the Forward Algorithm.vtt 4KB
  99. 3. Markov Models Example Problems and Applications/1. Example Problem Sick or Healthy.vtt 4KB
  100. 6. HMMs for Continuous Observations/2. Generating Data from a Real-Valued HMM.vtt 4KB
  101. 4. Hidden Markov Models for Discrete Observations/7. Visual Intuition for the Viterbi Algorithm.vtt 4KB
  102. 1. Introduction and Outline/4. How to Succeed in this Course.vtt 4KB
  103. 1. Introduction and Outline/2. Unsupervised or Supervised.vtt 4KB
  104. 4. Hidden Markov Models for Discrete Observations/6. The Viterbi Algorithm.vtt 3KB
  105. 10. Appendix/1. What is the Appendix.vtt 3KB
  106. 9. Basics Review/1. (Review) Gaussian Mixture Models.vtt 3KB
  107. 3. Markov Models Example Problems and Applications/2. Example Problem Expected number of continuously sick days.vtt 3KB
  108. 10. Appendix/12. BONUS Where to get Udemy coupons and FREE deep learning material.vtt 3KB
  109. 7. HMMs for Classification/1. Generative vs. Discriminative Classifiers.vtt 3KB
  110. 4. Hidden Markov Models for Discrete Observations/8. The Baum-Welch Algorithm.vtt 3KB
  111. 6. HMMs for Continuous Observations/4. Continuous-Observation HMM in Code (part 2).vtt 3KB
  112. 4. Hidden Markov Models for Discrete Observations/2. HMMs are Doubly Embedded.vtt 3KB
  113. 4. Hidden Markov Models for Discrete Observations/14. Scaled Viterbi Algorithm in Log Space.vtt 2KB
  114. 1. Introduction and Outline/3. Where to get the Code and Data.vtt 2KB
  115. Readme.txt 962B
  116. [GigaCourse.com].url 49B