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

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

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文件大小： 1.15G
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收录时间：2022-02-09
最近下载：2024-12-14

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文件列表

  • 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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