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[FreeCourseSite com] Udemy - Unsupervised Machine Learning Hidden Markov Models in Python
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Name:[FreeCourseSite com] Udemy - Unsupervised Machine Learning Hidden Markov Models in Python
Infohash: 01405C998EE031F0B1BF0D4DBA395C5D572E1092
Total Size: 1.15 GB
Magnet: Magnet Download
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Last Updated: 2026-01-18 12:05:34 (Update Now)
Torrent added: 2019-04-14 02:00:58
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Torrent Files List
1. Introduction and Outline (Size: 1.15 GB) (Files: 116)
1. Introduction and Outline
1. Introduction and Outline Why would you want to use an HMM.mp4
1. Introduction and Outline Why would you want to use an HMM.vtt
2. Unsupervised or Supervised.mp4
2. Unsupervised or Supervised.vtt
3. Where to get the Code and Data.mp4
3. Where to get the Code and Data.vtt
4. How to Succeed in this Course.mp4
4. How to Succeed in this Course.vtt
10. Appendix
1. What is the Appendix.mp4
1. What is the Appendix.vtt
10. What order should I take your courses in (part 1).mp4
10. What order should I take your courses in (part 1).vtt
11. What order should I take your courses in (part 2).mp4
11. What order should I take your courses in (part 2).vtt
12. BONUS Where to get Udemy coupons and FREE deep learning material.mp4
12. BONUS Where to get Udemy coupons and FREE deep learning material.vtt
2. Windows-Focused Environment Setup 2018.mp4
2. Windows-Focused Environment Setup 2018.vtt
3. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4
3. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.vtt
4. How to Code by Yourself (part 1).mp4
4. How to Code by Yourself (part 1).vtt
5. How to Code by Yourself (part 2).mp4
5. How to Code by Yourself (part 2).vtt
6. How to Succeed in this Course (Long Version).mp4
6. How to Succeed in this Course (Long Version).vtt
7. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4
7. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.vtt
8. Proof that using Jupyter Notebook is the same as not using it.mp4
8. Proof that using Jupyter Notebook is the same as not using it.vtt
9. Python 2 vs Python 3.mp4
9. Python 2 vs Python 3.vtt
2. Markov Models
1. The Markov Property.mp4
1. The Markov Property.vtt
2. Markov Models.mp4
2. Markov Models.vtt
3. The Math of Markov Chains.mp4
3. The Math of Markov Chains.vtt
3. Markov Models Example Problems and Applications
1. Example Problem Sick or Healthy.mp4
1. Example Problem Sick or Healthy.vtt
2. Example Problem Expected number of continuously sick days.mp4
2. Example Problem Expected number of continuously sick days.vtt
3. Example application SEO and Bounce Rate Optimization.mp4
3. Example application SEO and Bounce Rate Optimization.vtt
4. Example Application Build a 2nd-order language model and generate phrases.mp4
4. Example Application Build a 2nd-order language model and generate phrases.vtt
5. Example Application Google’s PageRank algorithm.mp4
5. Example Application Google’s PageRank algorithm.vtt
4. Hidden Markov Models for Discrete Observations
1. From Markov Models to Hidden Markov Models.mp4
1. From Markov Models to Hidden Markov Models.vtt
10. Baum-Welch Updates for Multiple Observations.mp4
10. Baum-Welch Updates for Multiple Observations.vtt
11. Discrete HMM in Code.mp4
11. Discrete HMM in Code.vtt
12. The underflow problem and how to solve it.mp4
12. The underflow problem and how to solve it.vtt
13. Discrete HMM Updates in Code with Scaling.mp4
13. Discrete HMM Updates in Code with Scaling.vtt
14. Scaled Viterbi Algorithm in Log Space.mp4
14. Scaled Viterbi Algorithm in Log Space.vtt
2. HMMs are Doubly Embedded.mp4
2. HMMs are Doubly Embedded.vtt
3. How can we choose the number of hidden states.mp4
3. How can we choose the number of hidden states.vtt
4. The Forward-Backward Algorithm.mp4
4. The Forward-Backward Algorithm.vtt
5. Visual Intuition for the Forward Algorithm.mp4
5. Visual Intuition for the Forward Algorithm.vtt
6. The Viterbi Algorithm.mp4
6. The Viterbi Algorithm.vtt
7. Visual Intuition for the Viterbi Algorithm.mp4
7. Visual Intuition for the Viterbi Algorithm.vtt
8. The Baum-Welch Algorithm.mp4
8. The Baum-Welch Algorithm.vtt
9. Baum-Welch Explanation and Intuition.mp4
9. Baum-Welch Explanation and Intuition.vtt
5. Discrete HMMs Using Deep Learning Libraries
1. Gradient Descent Tutorial.mp4
1. Gradient Descent Tutorial.vtt
2. Theano Scan Tutorial.mp4
2. Theano Scan Tutorial.vtt
3. Discrete HMM in Theano.mp4
3. Discrete HMM in Theano.vtt
4. Improving our Gradient Descent-Based HMM.mp4
4. Improving our Gradient Descent-Based HMM.vtt
5. Tensorflow Scan Tutorial.mp4
5. Tensorflow Scan Tutorial.vtt
6. Discrete HMM in Tensorflow.mp4
6. Discrete HMM in Tensorflow.vtt
6. HMMs for Continuous Observations
1. Gaussian Mixture Models with Hidden Markov Models.mp4
1. Gaussian Mixture Models with Hidden Markov Models.vtt
2. Generating Data from a Real-Valued HMM.mp4
2. Generating Data from a Real-Valued HMM.vtt
3. Continuous-Observation HMM in Code (part 1).mp4
3. Continuous-Observation HMM in Code (part 1).vtt
4. Continuous-Observation HMM in Code (part 2).mp4
4. Continuous-Observation HMM in Code (part 2).vtt
5. Continuous HMM in Theano.mp4
5. Continuous HMM in Theano.vtt
6. Continuous HMM in Tensorflow.mp4
6. Continuous HMM in Tensorflow.vtt
7. HMMs for Classification
1. Generative vs. Discriminative Classifiers.mp4
1. Generative vs. Discriminative Classifiers.vtt
2. HMM Classification on Poetry Data (Robert Frost vs. Edgar Allan Poe).mp4
2. HMM Classification on Poetry Data (Robert Frost vs. Edgar Allan Poe).vtt
8. Bonus Example Parts-of-Speech Tagging
1. Parts-of-Speech Tagging Concepts.mp4
1. Parts-of-Speech Tagging Concepts.vtt
2. POS Tagging with an HMM.mp4
2. POS Tagging with an HMM.vtt
9. Basics Review
1. (Review) Gaussian Mixture Models.mp4
1. (Review) Gaussian Mixture Models.vtt
2. (Review) Theano Tutorial.mp4
2. (Review) Theano Tutorial.vtt
3. (Review) Tensorflow Tutorial.mp4
3. (Review) Tensorflow Tutorial.vtt
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