Udemy - Unsupervised Machine Learning Hidden Markov Models in Python

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  • Last checkedDec. 18th '18
  • Date uploadedDec. 18th '18
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Unsupervised Machine Learning Hidden Markov Models in Python

HMMs for stock price analysis, language modeling, web analytics, biology, and PageRank.

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[DesireCourse.Com] Udemy - Unsupervised Machine Learning Hidden Markov Models in Python 01 Introduction and Outline
  • 001 Introduction and Outline Why would you want to use an HMM.mp4 (6.8 MB)
  • 002 Unsupervised or Supervised.mp4 (5.3 MB)
  • 003 Where to get the Code and Data.mp4 (2.1 MB)
  • 004 How to Succeed in this Course.mp4 (8.8 MB)
02 Markov Models
  • 005 The Markov Property.mp4 (8.3 MB)
  • 006 Markov Models.mp4 (8.2 MB)
  • 007 The Math of Markov Chains.mp4 (9.0 MB)
03 Markov Models Example Problems and Applications
  • 008 Example Problem Sick or Healthy.mp4 (5.5 MB)
  • 009 Example Problem Expected number of continuously sick days.mp4 (4.6 MB)
  • 010 Example application SEO and Bounce Rate Optimization.mp4 (15.8 MB)
  • 011 Example Application Build a 2nd-order language model and generate phrases.mp4 (26.9 MB)
  • 012 Example Application Googles PageRank algorithm.mp4 (8.7 MB)
04 Hidden Markov Models for Discrete Observations
  • 013 From Markov Models to Hidden Markov Models.mp4 (10.2 MB)
  • 014 HMMs are Doubly Embedded.mp4 (3.1 MB)
  • 015 How can we choose the number of hidden states.mp4 (7.3 MB)
  • 016 The Forward-Backward Algorithm.mp4 (6.8 MB)
  • 017 Visual Intuition for the Forward Algorithm.mp4 (6.0 MB)
  • 018 The Viterbi Algorithm.mp4 (5.0 MB)
  • 019 Visual Intuition for the Viterbi Algorithm.mp4 (5.7 MB)
  • 020 The Baum-Welch Algorithm.mp4 (4.3 MB)
  • 021 Baum-Welch Explanation and Intuition.mp4 (12.0 MB)
  • 022 Baum-Welch Updates for Multiple Observations.mp4 (7.5 MB)
  • 023 Discrete HMM in Code.mp4 (47.4 MB)
  • 024 The underflow problem and how to solve it.mp4 (7.7 MB)
  • 025 Discrete HMM Updates in Code with Scaling.mp4 (29.1 MB)
  • 026 Scaled Viterbi Algorithm in Log Space.mp4 (9.2 MB)
05 Discrete HMMs Using Deep Learning Libraries
  • 027 Gradient Descent Tutorial.mp4 (8.4 MB)
  • 028 Theano Scan Tutorial.mp4 (23.8 MB)
  • 029 Discrete HMM in Theano.mp4 (30.7 MB)
  • 030 Improving our Gradient Descent-Based HMM.mp4 (8.0 MB)
  • 031 Tensorflow Scan Tutorial.mp4 (23.1 MB)
  • 032 Discrete HMM in Tensorflow.mp4 (16.4 MB)
06 HMMs for Continuous Observations
  • 033 Gaussian Mixture Models with Hidden Markov Models.mp4 (6.3 MB)
  • 034 Generating Data from a Real-Valued HMM.mp4 (14.9 MB)
  • 035 Continuous-Observation HMM in Code part 1.mp4 (46.7 MB)
  • 036 Continuous-Observation HMM in Code part 2.mp4 (15.3 MB)
  • 037 Continuous HMM in Theano.mp4 (45.4 MB)
  • 038 Continuous HMM in Tensorflow.mp4 (22.5 MB)
07 HMMs for Classification
  • 039 Generative vs. Discriminative Classifiers.mp4 (4.1 MB)
  • 040 HMM Classification on Poetry Data Robert Frost vs. Edgar Allan Poe.mp4 (24.4 MB)
08 Bonus Example Parts-of-Speech Tagging
  • 041 Parts-of-Speech Tagging Concepts.mp4 (8.5 MB)
  • 042 POS Tagging with an HMM.mp4 (14.4 MB)
09 Appendix
  • 043 Review of Gaussian Mixture Models.mp4 (5.0 MB)
  • 044 Theano Tutorial.mp4 (19.9 MB)
  • 045 Tensorflow Tutorial.mp4 (13.9 MB)
  • 046 How to install Numpy Scipy Matplotlib Pandas IPython Theano and TensorFlow.mp4 (43.9 MB)
  • 047 How to Code by Yourself part 1.mp4 (24.5 MB)
  • 048 How to Code by Yourself part 2.mp4 (14.8 MB)
  • 049 BONUS Where to get Udemy coupons and FREE deep learning material.mp4 (4.0 MB)
  • [DesireCourse.Com].txt (0.7 KB)
  • [DesireCourse.Com].url (0.0 KB)

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