lyhsieh / NTHU-Machine-Learning

NTHU EE6550: Machine Learning

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NTHU EE6550 Machine Learning

Course Coverage

  • Probability Distributions
  • Linear Models for Regression
  • Linear Models for Classification
  • Neural Networks
  • Kernel Methods
  • Sparse Kernel Machine
  • Graphical Models
  • Mixture Models & EM
  • Sampling Methods

Homework

Title Dataset
HW1 Maximum A Posteriori (MAP) wine
HW2 Maximum Likelihood and Bayesian Linear Regression graduate admissions
HW3 Neural Network from Scratch fruit

Final Project

Behavior Classification of Exposition Visitors (Link)

About

NTHU EE6550: Machine Learning

License:MIT License


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Language:Jupyter Notebook 99.8%Language:Python 0.2%