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[GigaCourse.com] Udemy - Unsupervised Machine Learning Hidden Markov Models in Python
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文档列表
10. Appendix/2. Windows-Focused Environment Setup 2018.mp4
195.4 MB
10. Appendix/8. Proof that using Jupyter Notebook is the same as not using it.mp4
82.1 MB
4. Hidden Markov Models for Discrete Observations/11. Discrete HMM in Code.mp4
49.7 MB
6. HMMs for Continuous Observations/3. Continuous-Observation HMM in Code (part 1).mp4
49.0 MB
6. HMMs for Continuous Observations/5. Continuous HMM in Theano.mp4
47.6 MB
10. Appendix/3. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4
46.0 MB
10. Appendix/7. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4
40.9 MB
10. Appendix/11. What order should I take your courses in (part 2).mp4
39.5 MB
5. Discrete HMMs Using Deep Learning Libraries/3. Discrete HMM in Theano.mp4
32.2 MB
10. Appendix/10. What order should I take your courses in (part 1).mp4
30.8 MB
4. Hidden Markov Models for Discrete Observations/13. Discrete HMM Updates in Code with Scaling.mp4
30.6 MB
3. Markov Models Example Problems and Applications/4. Example Application Build a 2nd-order language model and generate phrases.mp4
28.2 MB
5. Discrete HMMs Using Deep Learning Libraries/4. Improving our Gradient Descent-Based HMM.mp4
27.2 MB
10. Appendix/4. How to Code by Yourself (part 1).mp4
25.7 MB
7. HMMs for Classification/2. HMM Classification on Poetry Data (Robert Frost vs. Edgar Allan Poe).mp4
25.6 MB
5. Discrete HMMs Using Deep Learning Libraries/2. Theano Scan Tutorial.mp4
24.9 MB
5. Discrete HMMs Using Deep Learning Libraries/5. Tensorflow Scan Tutorial.mp4
24.2 MB
5. Discrete HMMs Using Deep Learning Libraries/1. Gradient Descent Tutorial.mp4
23.9 MB
6. HMMs for Continuous Observations/6. Continuous HMM in Tensorflow.mp4
23.6 MB
4. Hidden Markov Models for Discrete Observations/4. The Forward-Backward Algorithm.mp4
23.5 MB
9. Basics Review/2. (Review) Theano Tutorial.mp4
20.8 MB
10. Appendix/6. How to Succeed in this Course (Long Version).mp4
19.2 MB
6. HMMs for Continuous Observations/1. Gaussian Mixture Models with Hidden Markov Models.mp4
17.3 MB
5. Discrete HMMs Using Deep Learning Libraries/6. Discrete HMM in Tensorflow.mp4
17.2 MB
3. Markov Models Example Problems and Applications/3. Example application SEO and Bounce Rate Optimization.mp4
16.6 MB
4. Hidden Markov Models for Discrete Observations/7. Visual Intuition for the Viterbi Algorithm.mp4
16.4 MB
6. HMMs for Continuous Observations/4. Continuous-Observation HMM in Code (part 2).mp4
16.0 MB
6. HMMs for Continuous Observations/2. Generating Data from a Real-Valued HMM.mp4
15.7 MB
10. Appendix/5. How to Code by Yourself (part 2).mp4
15.5 MB
8. Bonus Example Parts-of-Speech Tagging/2. POS Tagging with an HMM.mp4
15.1 MB
9. Basics Review/3. (Review) Tensorflow Tutorial.mp4
14.6 MB
4. Hidden Markov Models for Discrete Observations/9. Baum-Welch Explanation and Intuition.mp4
12.6 MB
4. Hidden Markov Models for Discrete Observations/1. From Markov Models to Hidden Markov Models.mp4
10.7 MB
4. Hidden Markov Models for Discrete Observations/14. Scaled Viterbi Algorithm in Log Space.mp4
9.7 MB
2. Markov Models/3. The Math of Markov Chains.mp4
9.5 MB
3. Markov Models Example Problems and Applications/5. Example Application Google’s PageRank algorithm.mp4
9.1 MB
8. Bonus Example Parts-of-Speech Tagging/1. Parts-of-Speech Tagging Concepts.mp4
8.9 MB
2. Markov Models/1. The Markov Property.mp4
8.7 MB
2. Markov Models/2. Markov Models.mp4
8.6 MB
10. Appendix/9. Python 2 vs Python 3.mp4
8.2 MB
4. Hidden Markov Models for Discrete Observations/12. The underflow problem and how to solve it.mp4
8.0 MB
4. Hidden Markov Models for Discrete Observations/10. Baum-Welch Updates for Multiple Observations.mp4
7.8 MB
4. Hidden Markov Models for Discrete Observations/3. How can we choose the number of hidden states.mp4
7.7 MB
1. Introduction and Outline/1. Introduction and Outline Why would you want to use an HMM.mp4
7.1 MB
4. Hidden Markov Models for Discrete Observations/5. Visual Intuition for the Forward Algorithm.mp4
6.3 MB
3. Markov Models Example Problems and Applications/1. Example Problem Sick or Healthy.mp4
5.8 MB
10. Appendix/1. What is the Appendix.mp4
5.7 MB
1. Introduction and Outline/2. Unsupervised or Supervised.mp4
5.5 MB
4. Hidden Markov Models for Discrete Observations/6. The Viterbi Algorithm.mp4
5.3 MB
9. Basics Review/1. (Review) Gaussian Mixture Models.mp4
5.2 MB
3. Markov Models Example Problems and Applications/2. Example Problem Expected number of continuously sick days.mp4
4.9 MB
4. Hidden Markov Models for Discrete Observations/8. The Baum-Welch Algorithm.mp4
4.6 MB
7. HMMs for Classification/1. Generative vs. Discriminative Classifiers.mp4
4.3 MB
10. Appendix/12. BONUS Where to get Udemy coupons and FREE deep learning material.mp4
4.2 MB
1. Introduction and Outline/4. How to Succeed in this Course.mp4
3.5 MB
1. Introduction and Outline/3. Where to get the Code and Data.mp4
2.2 MB
4. Hidden Markov Models for Discrete Observations/2. HMMs are Doubly Embedded.mp4
1.6 MB
10. Appendix/7. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.vtt
30.6 kB
10. Appendix/11. What order should I take your courses in (part 2).vtt
22.8 kB
10. Appendix/4. How to Code by Yourself (part 1).vtt
21.8 kB
10. Appendix/2. Windows-Focused Environment Setup 2018.vtt
19.1 kB
10. Appendix/10. What order should I take your courses in (part 1).vtt
15.5 kB
5. Discrete HMMs Using Deep Learning Libraries/5. Tensorflow Scan Tutorial.vtt
14.4 kB
10. Appendix/6. How to Succeed in this Course (Long Version).vtt
14.0 kB
4. Hidden Markov Models for Discrete Observations/11. Discrete HMM in Code.vtt
13.8 kB
10. Appendix/3. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.vtt
13.7 kB
10. Appendix/8. Proof that using Jupyter Notebook is the same as not using it.vtt
13.5 kB
10. Appendix/5. How to Code by Yourself (part 2).vtt
12.7 kB
3. Markov Models Example Problems and Applications/4. Example Application Build a 2nd-order language model and generate phrases.vtt
12.6 kB
6. HMMs for Continuous Observations/3. Continuous-Observation HMM in Code (part 1).vtt
11.6 kB
5. Discrete HMMs Using Deep Learning Libraries/2. Theano Scan Tutorial.vtt
11.5 kB
6. HMMs for Continuous Observations/5. Continuous HMM in Theano.vtt
10.7 kB
6. HMMs for Continuous Observations/6. Continuous HMM in Tensorflow.vtt
10.6 kB
3. Markov Models Example Problems and Applications/3. Example application SEO and Bounce Rate Optimization.vtt
9.7 kB
5. Discrete HMMs Using Deep Learning Libraries/6. Discrete HMM in Tensorflow.vtt
8.6 kB
4. Hidden Markov Models for Discrete Observations/9. Baum-Welch Explanation and Intuition.vtt
8.3 kB
4. Hidden Markov Models for Discrete Observations/1. From Markov Models to Hidden Markov Models.vtt
8.1 kB
4. Hidden Markov Models for Discrete Observations/13. Discrete HMM Updates in Code with Scaling.vtt
8.0 kB
7. HMMs for Classification/2. HMM Classification on Poetry Data (Robert Frost vs. Edgar Allan Poe).vtt
8.0 kB
5. Discrete HMMs Using Deep Learning Libraries/3. Discrete HMM in Theano.vtt
7.6 kB
9. Basics Review/2. (Review) Theano Tutorial.vtt
7.2 kB
2. Markov Models/3. The Math of Markov Chains.vtt
6.9 kB
3. Markov Models Example Problems and Applications/5. Example Application Google’s PageRank algorithm.vtt
6.7 kB
8. Bonus Example Parts-of-Speech Tagging/1. Parts-of-Speech Tagging Concepts.vtt
6.5 kB
2. Markov Models/1. The Markov Property.vtt
6.4 kB
4. Hidden Markov Models for Discrete Observations/12. The underflow problem and how to solve it.vtt
6.3 kB
2. Markov Models/2. Markov Models.vtt
6.1 kB
5. Discrete HMMs Using Deep Learning Libraries/4. Improving our Gradient Descent-Based HMM.vtt
6.0 kB
10. Appendix/9. Python 2 vs Python 3.vtt
6.0 kB
9. Basics Review/3. (Review) Tensorflow Tutorial.vtt
5.7 kB
4. Hidden Markov Models for Discrete Observations/10. Baum-Welch Updates for Multiple Observations.vtt
5.7 kB
4. Hidden Markov Models for Discrete Observations/3. How can we choose the number of hidden states.vtt
5.7 kB
1. Introduction and Outline/1. Introduction and Outline Why would you want to use an HMM.vtt
5.6 kB
4. Hidden Markov Models for Discrete Observations/4. The Forward-Backward Algorithm.vtt
5.3 kB
5. Discrete HMMs Using Deep Learning Libraries/1. Gradient Descent Tutorial.vtt
5.3 kB
6. HMMs for Continuous Observations/1. Gaussian Mixture Models with Hidden Markov Models.vtt
5.0 kB
8. Bonus Example Parts-of-Speech Tagging/2. POS Tagging with an HMM.vtt
4.7 kB
4. Hidden Markov Models for Discrete Observations/5. Visual Intuition for the Forward Algorithm.vtt
4.6 kB
3. Markov Models Example Problems and Applications/1. Example Problem Sick or Healthy.vtt
4.4 kB
6. HMMs for Continuous Observations/2. Generating Data from a Real-Valued HMM.vtt
4.1 kB
4. Hidden Markov Models for Discrete Observations/7. Visual Intuition for the Viterbi Algorithm.vtt
4.0 kB
1. Introduction and Outline/4. How to Succeed in this Course.vtt
3.8 kB
1. Introduction and Outline/2. Unsupervised or Supervised.vtt
3.8 kB
4. Hidden Markov Models for Discrete Observations/6. The Viterbi Algorithm.vtt
3.6 kB
10. Appendix/1. What is the Appendix.vtt
3.5 kB
9. Basics Review/1. (Review) Gaussian Mixture Models.vtt
3.4 kB
3. Markov Models Example Problems and Applications/2. Example Problem Expected number of continuously sick days.vtt
3.4 kB
10. Appendix/12. BONUS Where to get Udemy coupons and FREE deep learning material.vtt
3.4 kB
7. HMMs for Classification/1. Generative vs. Discriminative Classifiers.vtt
3.3 kB
4. Hidden Markov Models for Discrete Observations/8. The Baum-Welch Algorithm.vtt
3.0 kB
6. HMMs for Continuous Observations/4. Continuous-Observation HMM in Code (part 2).vtt
3.0 kB
4. Hidden Markov Models for Discrete Observations/2. HMMs are Doubly Embedded.vtt
2.7 kB
4. Hidden Markov Models for Discrete Observations/14. Scaled Viterbi Algorithm in Log Space.vtt
2.5 kB
1. Introduction and Outline/3. Where to get the Code and Data.vtt
1.8 kB
Readme.txt
962 Bytes
[GigaCourse.com].url
49 Bytes
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