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Machine Learning

Summer 2024, EE231001 Machine Learning, 孫民(SUN, MIN)
This course introduces the basic mathematical theoretical basis of machine learning and its application in different fields (such as pattern recognition, signal processing and data analysis and statistics).practical application).

Homeworks

Assignment 1- 95/100
Assignment 2- 96/100

Syllabus

  1. Introduction to machine learning
  2. Probability distributions
  3. Linear regression models
  4. Linear classification models
  5. Neural networks
  6. Kernel methods
  7. Graphical models
  8. Mixture models and EM
  9. Ensemble Learning

Refrence

Christopher M. Bishop, Pattern Recognition and Machine Learning, Springer, 2006, ISBN: 0387310738

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NTHU Machine Learning

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