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Udemy - Unsupervised Machine Learning Hidden Markov Models in Python (11.2023)

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Udemy - Unsupervised Machine Learning Hidden Markov Models in Python (11.2023)

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收录时间:2025-07-09
最近下载:2025-08-09

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文件列表

  • 10 - Setting Up Your Environment (FAQ by Student Request)/002 Anaconda Environment Setup.mp4 176.2 MB
  • 10 - Setting Up Your Environment (FAQ by Student Request)/003 How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 114.5 MB
  • 12 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/004 Machine Learning and AI Prerequisite Roadmap (pt 2).mp4 85.1 MB
  • 01 - Introduction and Outline/002 Where to get the Code and Data.mp4 76.8 MB
  • 04 - Hidden Markov Models for Discrete Observations/016 Discrete HMM in Code.mp4 72.9 MB
  • 06 - HMMs for Continuous Observations/006 Continuous HMM in Tensorflow.mp4 68.4 MB
  • 06 - HMMs for Continuous Observations/005 Continuous HMM in Theano.mp4 67.4 MB
  • 02 - Markov Models/004 The Math of Markov Chains.mp4 61.8 MB
  • 11 - Extra Help With Python Coding for Beginners (FAQ by Student Request)/001 How to Code by Yourself (part 1).mp4 58.8 MB
  • 06 - HMMs for Continuous Observations/003 Continuous-Observation HMM in Code (part 1).mp4 56.9 MB
  • 05 - Discrete HMMs Using Deep Learning Libraries/006 Discrete HMM in Tensorflow.mp4 53.0 MB
  • 02 - Markov Models/002 Markov Models.mp4 48.1 MB
  • 12 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/002 Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 44.5 MB
  • 06 - HMMs for Continuous Observations/004 Continuous-Observation HMM in Code (part 2).mp4 43.7 MB
  • 05 - Discrete HMMs Using Deep Learning Libraries/005 Tensorflow Scan Tutorial.mp4 43.5 MB
  • 09 - Theano, Tensorflow, and Machine Learning Basics Review/002 (Review) Theano Tutorial.mp4 42.7 MB
  • 13 - Appendix FAQ Finale/002 BONUS.mp4 41.9 MB
  • 11 - Extra Help With Python Coding for Beginners (FAQ by Student Request)/003 Proof that using Jupyter Notebook is the same as not using it.mp4 38.9 MB
  • 07 - HMMs for Classification/003 HMM Classification on Poetry Data (Robert Frost vs. Edgar Allan Poe).mp4 36.4 MB
  • 04 - Hidden Markov Models for Discrete Observations/018 Discrete HMM Updates in Code with Scaling.mp4 35.9 MB
  • 01 - Introduction and Outline/001 Introduction and Outline Why would you want to use an HMM.mp4 35.8 MB
  • 02 - Markov Models/003 Probability Smoothing and Log-Space.mp4 35.7 MB
  • 05 - Discrete HMMs Using Deep Learning Libraries/003 Discrete HMM in Theano.mp4 35.3 MB
  • 05 - Discrete HMMs Using Deep Learning Libraries/002 Theano Scan Tutorial.mp4 35.3 MB
  • 02 - Markov Models/001 The Markov Property.mp4 33.8 MB
  • 03 - Markov Models Example Problems and Applications/003 Example application SEO and Bounce Rate Optimization.mp4 31.2 MB
  • 03 - Markov Models Example Problems and Applications/004 Example Application Build a 2nd-order language model and generate phrases.mp4 31.1 MB
  • 12 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/003 Machine Learning and AI Prerequisite Roadmap (pt 1).mp4 28.8 MB
  • 04 - Hidden Markov Models for Discrete Observations/012 HMM Training (part 3).mp4 28.6 MB
  • 03 - Markov Models Example Problems and Applications/006 Suggestion Box.mp4 28.5 MB
  • 04 - Hidden Markov Models for Discrete Observations/005 The Forward-Backward Algorithm (part 1).mp4 27.3 MB
  • 04 - Hidden Markov Models for Discrete Observations/009 The Viterbi Algorithm (part 2).mp4 25.2 MB
  • 09 - Theano, Tensorflow, and Machine Learning Basics Review/003 (Review) Tensorflow Tutorial.mp4 24.5 MB
  • 04 - Hidden Markov Models for Discrete Observations/013 HMM Training (part 4).mp4 22.9 MB
  • 06 - HMMs for Continuous Observations/002 Generating Data from a Real-Valued HMM.mp4 22.0 MB
  • 11 - Extra Help With Python Coding for Beginners (FAQ by Student Request)/002 How to Code by Yourself (part 2).mp4 21.9 MB
  • 12 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/001 How to Succeed in this Course (Long Version).mp4 18.7 MB
  • 01 - Introduction and Outline/003 How to Succeed in this Course.mp4 17.0 MB
  • 04 - Hidden Markov Models for Discrete Observations/011 HMM Training (part 2).mp4 16.7 MB
  • 08 - Bonus Example Parts-of-Speech Tagging/002 POS Tagging with an HMM.mp4 16.1 MB
  • 05 - Discrete HMMs Using Deep Learning Libraries/001 Gradient Descent Tutorial.mp4 15.9 MB
  • 04 - Hidden Markov Models for Discrete Observations/002 HMM - Basic Examples.mp4 15.8 MB
  • 04 - Hidden Markov Models for Discrete Observations/014 How to Choose the Number of Hidden States.mp4 14.0 MB
  • 04 - Hidden Markov Models for Discrete Observations/003 Parameters of an HMM.mp4 13.3 MB
  • 03 - Markov Models Example Problems and Applications/005 Example Application Google’s PageRank algorithm.mp4 12.9 MB
  • 04 - Hidden Markov Models for Discrete Observations/007 The Forward-Backward Algorithm (part 3).mp4 12.6 MB
  • 04 - Hidden Markov Models for Discrete Observations/001 From Markov Models to Hidden Markov Models.mp4 12.1 MB
  • 04 - Hidden Markov Models for Discrete Observations/006 The Forward-Backward Algorithm (part 2).mp4 11.8 MB
  • 04 - Hidden Markov Models for Discrete Observations/019 Scaled Viterbi Algorithm in Log Space.mp4 11.5 MB
  • 04 - Hidden Markov Models for Discrete Observations/008 The Viterbi Algorithm (part 1).mp4 11.0 MB
  • 04 - Hidden Markov Models for Discrete Observations/004 The 3 Problems of an HMM.mp4 10.8 MB
  • 05 - Discrete HMMs Using Deep Learning Libraries/004 Improving our Gradient Descent-Based HMM.mp4 10.6 MB
  • 08 - Bonus Example Parts-of-Speech Tagging/001 Parts-of-Speech Tagging Concepts.mp4 10.2 MB
  • 04 - Hidden Markov Models for Discrete Observations/017 The underflow problem and how to solve it.mp4 9.9 MB
  • 10 - Setting Up Your Environment (FAQ by Student Request)/001 Pre-Installation Check.mp4 9.4 MB
  • 04 - Hidden Markov Models for Discrete Observations/015 Baum-Welch Updates for Multiple Observations.mp4 9.3 MB
  • 04 - Hidden Markov Models for Discrete Observations/010 HMM Training (part 1).mp4 8.5 MB
  • 11 - Extra Help With Python Coding for Beginners (FAQ by Student Request)/004 Python 2 vs Python 3.mp4 8.0 MB
  • 06 - HMMs for Continuous Observations/001 Gaussian Mixture Models with Hidden Markov Models.mp4 7.5 MB
  • 07 - HMMs for Classification/001 Unsupervised or Supervised.mp4 7.0 MB
  • 13 - Appendix FAQ Finale/001 What is the Appendix.mp4 6.4 MB
  • 07 - HMMs for Classification/002 Generative vs. Discriminative Classifiers.mp4 5.6 MB
  • 03 - Markov Models Example Problems and Applications/001 Example Problem Sick or Healthy.mp4 5.4 MB
  • 09 - Theano, Tensorflow, and Machine Learning Basics Review/001 (Review) Gaussian Mixture Models.mp4 4.9 MB
  • 03 - Markov Models Example Problems and Applications/002 Example Problem Expected number of continuously sick days.mp4 4.5 MB
  • 12 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/002 Is this for Beginners or Experts Academic or Practical Fast or slow-paced.srt 32.6 kB
  • 12 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/004 Machine Learning and AI Prerequisite Roadmap (pt 2).srt 24.1 kB
  • 11 - Extra Help With Python Coding for Beginners (FAQ by Student Request)/001 How to Code by Yourself (part 1).srt 23.1 kB
  • 04 - Hidden Markov Models for Discrete Observations/005 The Forward-Backward Algorithm (part 1).srt 20.4 kB
  • 10 - Setting Up Your Environment (FAQ by Student Request)/002 Anaconda Environment Setup.srt 20.2 kB
  • 02 - Markov Models/004 The Math of Markov Chains.srt 19.8 kB
  • 04 - Hidden Markov Models for Discrete Observations/009 The Viterbi Algorithm (part 2).srt 18.6 kB
  • 01 - Introduction and Outline/002 Where to get the Code and Data.srt 17.3 kB
  • 12 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/003 Machine Learning and AI Prerequisite Roadmap (pt 1).srt 17.0 kB
  • 02 - Markov Models/002 Markov Models.srt 16.9 kB
  • 04 - Hidden Markov Models for Discrete Observations/012 HMM Training (part 3).srt 16.5 kB
  • 05 - Discrete HMMs Using Deep Learning Libraries/005 Tensorflow Scan Tutorial.srt 15.4 kB
  • 04 - Hidden Markov Models for Discrete Observations/016 Discrete HMM in Code.srt 15.1 kB
  • 12 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/001 How to Succeed in this Course (Long Version).srt 15.1 kB
  • 10 - Setting Up Your Environment (FAQ by Student Request)/003 How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.srt 14.6 kB
  • 11 - Extra Help With Python Coding for Beginners (FAQ by Student Request)/003 Proof that using Jupyter Notebook is the same as not using it.srt 14.4 kB
  • 04 - Hidden Markov Models for Discrete Observations/013 HMM Training (part 4).srt 14.1 kB
  • 03 - Markov Models Example Problems and Applications/004 Example Application Build a 2nd-order language model and generate phrases.srt 13.7 kB
  • 11 - Extra Help With Python Coding for Beginners (FAQ by Student Request)/002 How to Code by Yourself (part 2).srt 13.6 kB
  • 06 - HMMs for Continuous Observations/003 Continuous-Observation HMM in Code (part 1).srt 12.7 kB
  • 05 - Discrete HMMs Using Deep Learning Libraries/002 Theano Scan Tutorial.srt 12.5 kB
  • 04 - Hidden Markov Models for Discrete Observations/011 HMM Training (part 2).srt 11.9 kB
  • 06 - HMMs for Continuous Observations/005 Continuous HMM in Theano.srt 11.6 kB
  • 06 - HMMs for Continuous Observations/006 Continuous HMM in Tensorflow.srt 11.0 kB
  • 02 - Markov Models/003 Probability Smoothing and Log-Space.srt 10.5 kB
  • 04 - Hidden Markov Models for Discrete Observations/002 HMM - Basic Examples.srt 10.5 kB
  • 03 - Markov Models Example Problems and Applications/003 Example application SEO and Bounce Rate Optimization.srt 10.5 kB
  • 02 - Markov Models/001 The Markov Property.srt 9.7 kB
  • 04 - Hidden Markov Models for Discrete Observations/014 How to Choose the Number of Hidden States.srt 9.5 kB
  • 04 - Hidden Markov Models for Discrete Observations/003 Parameters of an HMM.srt 9.3 kB
  • 04 - Hidden Markov Models for Discrete Observations/007 The Forward-Backward Algorithm (part 3).srt 9.3 kB
  • 05 - Discrete HMMs Using Deep Learning Libraries/006 Discrete HMM in Tensorflow.srt 9.0 kB
  • 04 - Hidden Markov Models for Discrete Observations/018 Discrete HMM Updates in Code with Scaling.srt 8.8 kB
  • 04 - Hidden Markov Models for Discrete Observations/006 The Forward-Backward Algorithm (part 2).srt 8.7 kB
  • 04 - Hidden Markov Models for Discrete Observations/001 From Markov Models to Hidden Markov Models.srt 8.7 kB
  • 07 - HMMs for Classification/003 HMM Classification on Poetry Data (Robert Frost vs. Edgar Allan Poe).srt 8.6 kB
  • 05 - Discrete HMMs Using Deep Learning Libraries/003 Discrete HMM in Theano.srt 8.2 kB
  • 13 - Appendix FAQ Finale/002 BONUS.srt 8.0 kB
  • 04 - Hidden Markov Models for Discrete Observations/004 The 3 Problems of an HMM.srt 7.7 kB
  • 04 - Hidden Markov Models for Discrete Observations/008 The Viterbi Algorithm (part 1).srt 7.5 kB
  • 09 - Theano, Tensorflow, and Machine Learning Basics Review/002 (Review) Theano Tutorial.srt 7.5 kB
  • 03 - Markov Models Example Problems and Applications/005 Example Application Google’s PageRank algorithm.srt 7.2 kB
  • 08 - Bonus Example Parts-of-Speech Tagging/001 Parts-of-Speech Tagging Concepts.srt 6.9 kB
  • 10 - Setting Up Your Environment (FAQ by Student Request)/001 Pre-Installation Check.srt 6.8 kB
  • 04 - Hidden Markov Models for Discrete Observations/017 The underflow problem and how to solve it.srt 6.7 kB
  • 01 - Introduction and Outline/001 Introduction and Outline Why would you want to use an HMM.srt 6.6 kB
  • 05 - Discrete HMMs Using Deep Learning Libraries/004 Improving our Gradient Descent-Based HMM.srt 6.5 kB
  • 11 - Extra Help With Python Coding for Beginners (FAQ by Student Request)/004 Python 2 vs Python 3.srt 6.2 kB
  • 09 - Theano, Tensorflow, and Machine Learning Basics Review/003 (Review) Tensorflow Tutorial.srt 6.1 kB
  • 04 - Hidden Markov Models for Discrete Observations/015 Baum-Welch Updates for Multiple Observations.srt 6.0 kB
  • 04 - Hidden Markov Models for Discrete Observations/010 HMM Training (part 1).srt 5.7 kB
  • 05 - Discrete HMMs Using Deep Learning Libraries/001 Gradient Descent Tutorial.srt 5.6 kB
  • 06 - HMMs for Continuous Observations/001 Gaussian Mixture Models with Hidden Markov Models.srt 5.4 kB
  • 08 - Bonus Example Parts-of-Speech Tagging/002 POS Tagging with an HMM.srt 5.1 kB
  • 03 - Markov Models Example Problems and Applications/006 Suggestion Box.srt 4.9 kB
  • 03 - Markov Models Example Problems and Applications/001 Example Problem Sick or Healthy.srt 4.8 kB
  • 01 - Introduction and Outline/003 How to Succeed in this Course.srt 4.5 kB
  • 06 - HMMs for Continuous Observations/002 Generating Data from a Real-Valued HMM.srt 4.5 kB
  • 07 - HMMs for Classification/001 Unsupervised or Supervised.srt 4.0 kB
  • 13 - Appendix FAQ Finale/001 What is the Appendix.srt 3.9 kB
  • 03 - Markov Models Example Problems and Applications/002 Example Problem Expected number of continuously sick days.srt 3.6 kB
  • 09 - Theano, Tensorflow, and Machine Learning Basics Review/001 (Review) Gaussian Mixture Models.srt 3.6 kB
  • 07 - HMMs for Classification/002 Generative vs. Discriminative Classifiers.srt 3.6 kB
  • 06 - HMMs for Continuous Observations/004 Continuous-Observation HMM in Code (part 2).srt 3.3 kB
  • 04 - Hidden Markov Models for Discrete Observations/019 Scaled Viterbi Algorithm in Log Space.srt 2.7 kB
  • 01 - Introduction and Outline/002 Github-Link.url 105 Bytes
  • 01 - Introduction and Outline/external-links.txt 102 Bytes

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