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

Files:

• 1. Introduction and Outline Why would you want to use an HMM.mp4 (6.8 MB)
• 1. Introduction and Outline Why would you want to use an HMM.vtt (5.4 KB)
• 2. Unsupervised or Supervised.mp4 (5.3 MB)
• 2. Unsupervised or Supervised.vtt (3.7 KB)
• 3. Where to get the Code and Data.mp4 (2.1 MB)
• 3. Where to get the Code and Data.vtt (1.7 KB)
• 4. How to Succeed in this Course.mp4 (3.3 MB)
• 4. How to Succeed in this Course.vtt (3.7 KB)

• 1. What is the Appendix.mp4 (5.5 MB)
• 1. What is the Appendix.vtt (3.4 KB)
• 10. What order should I take your courses in (part 1).mp4 (29.3 MB)
• 10. What order should I take your courses in (part 1).vtt (15.2 KB)
• 11. What order should I take your courses in (part 2).mp4 (37.6 MB)
• 11. What order should I take your courses in (part 2).vtt (22.3 KB)
• 12. BONUS Where to get Udemy coupons and FREE deep learning material.mp4 (4.0 MB)
• 12. BONUS Where to get Udemy coupons and FREE deep learning material.vtt (3.3 KB)
• 2. Windows-Focused Environment Setup 2018.mp4 (186.3 MB)
• 2. Windows-Focused Environment Setup 2018.vtt (18.7 KB)
• 3. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 (43.9 MB)
• 3. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.vtt (13.4 KB)
• 4. How to Code by Yourself (part 1).mp4 (24.5 MB)
• 4. How to Code by Yourself (part 1).vtt (21.3 KB)
• 5. How to Code by Yourself (part 2).mp4 (14.8 MB)
• 5. How to Code by Yourself (part 2).vtt (12.4 KB)
• 6. How to Succeed in this Course (Long Version).mp4 (18.3 MB)
• 6. How to Succeed in this Course (Long Version).vtt (13.7 KB)
• 7. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 (39.0 MB)
• 7. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.vtt (29.9 KB)
• 8. Proof that using Jupyter Notebook is the same as not using it.mp4 (78.3 MB)
• 8. Proof that using Jupyter Notebook is the same as not using it.vtt (13.2 KB)
• 9. Python 2 vs Python 3.mp4 (7.8 MB)
• 9. Python 2 vs Python 3.vtt (5.9 KB)

• 1. The Markov Property.mp4 (8.3 MB)
• 1. The Markov Property.vtt (6.2 KB)
• 2. Markov Models.mp4 (8.2 MB)
• 2. Markov Models.vtt (5.9 KB)
• 3. The Math of Markov Chains.mp4 (9.0 MB)
• 3. The Math of Markov Chains.vtt (6.7 KB)

• 1. Example Problem Sick or Healthy.mp4 (5.5 MB)
• 1. Example Problem Sick or Healthy.vtt (4.3 KB)
• 2. Example Problem Expected number of continuously sick days.mp4 (4.6 MB)
• 2. Example Problem Expected number of continuously sick days.vtt (3.3 KB)
• 3. Example application SEO and Bounce Rate Optimization.mp4 (15.8 MB)
• 3. Example application SEO and Bounce Rate Optimization.vtt (9.5 KB)
• 4. Example Application Build a 2nd-order language model and generate phrases.mp4 (26.9 MB)
• 4. Example Application Build a 2nd-order language model and generate phrases.vtt (12.3 KB)
• 5. Example Application Google’s PageRank algorithm.mp4 (8.7 MB)
• 5. Example Application Google’s PageRank algorithm.vtt (6.5 KB)

• 1. From Markov Models to Hidden Markov Models.mp4 (10.2 MB)
• 1. From Markov Models to Hidden Markov Models.vtt (7.9 KB)
• 10. Baum-Welch Updates for Multiple Observations.mp4 (7.5 MB)
• 10. Baum-Welch Updates for Multiple Observations.vtt (5.6 KB)
• 11. Discrete HMM in Code.mp4 (47.4 MB)
• 11. Discrete HMM in Code.vtt (13.5 KB)
• 12. The underflow problem and how to solve it.mp4 (7.7 MB)
• 12. The underflow problem and how to solve it.vtt (6.1 KB)
• 13. Discrete HMM Updates in Code with Scaling.mp4 (29.1 MB)
• 13. Discrete HMM Updates in Code with Scaling.vtt (7.8 KB)
• 14. Scaled Viterbi Algorithm in Log Space.mp4 (9.2 MB)
• 14. Scaled Viterbi Algorithm in Log Space.vtt (2.4 KB)
• 2. HMMs are Doubly Embedded.mp4 (1.5 MB)
• 2. HMMs are Doubly Embedded.vtt (2.6 KB)
• 3. How can we choose the number of hidden states.mp4 (7.3 MB)
• 3. How can we choose the number of hidden states.vtt (5.6 KB)
• 4. The Forward-Backward Algorithm.mp4 (22.4 MB)
• 4. The Forward-Backward Algorithm.vtt (5.2 KB)
• 5. Visual Intuition for the Forward Algorithm.mp4 (6.0 MB)
• 5. Visual Intuition for the Forward Algorithm.vtt (4.5 KB)
• 6. The Viterbi Algorithm.mp4 (5.0 MB)
• 6. The Viterbi Algorithm.vtt (3.5 KB)
• 7. Visual Intuition for the Viterbi Algorithm.mp4 (15.7 MB)
• 7. Visual Intuition for the Viterbi Algorithm.vtt (3.9 KB)
• 8. The Baum-Welch Algorithm.mp4 (4.3 MB)
• 8. The Baum-Welch Algorithm.vtt (3.0 KB)
• 9. Baum-Welch Explanation and Intuition.mp4 (12.0 MB)
• 9. Baum-Welch Explanation and Intuition.vtt (8.1 KB)

• 1. Gradient Descent Tutorial.mp4 (22.8 MB)
• 1. Gradient Descent Tutorial.vtt (5.2 KB)
• 2. Theano Scan Tutorial.mp4 (23.8 MB)
• 2. Theano Scan Tutorial.vtt (11.3 KB)
• 3. Discrete HMM in Theano.mp4 (30.7 MB)
• 3. Discrete HMM in Theano.vtt (7.4 KB)
• 4. Improving our Gradient Descent-Based HMM.mp4 (25.9 MB)
• 4. Improving our Gradient Descent-Based HMM.vtt (5.9 KB)
• 5. Tensorflow Scan Tutorial.mp4 (23.1 MB)
• 5. Tensorflow Scan Tutorial.vtt (14.0 KB)
• 6. Discrete HMM in Tensorflow.mp4 (16.4 MB)
• 6. Discrete HMM in Tensorflow.vtt (8.4 KB)

• 1. Gaussian Mixture Models with Hidden Markov Models.mp4 (16.5 MB)
• 1. Gaussian Mixture Models with Hidden Markov Models.vtt (4.9 KB)
• 2. Generating Data from a Real-Valued HMM.mp4 (14.9 MB)
• 2. Generating Data from a Real-Valued HMM.vtt (4.0 KB)
• 3. Continuous-Observat