Jeiyoon / ml

Machine Learning

About Me: https://jeiyoon.github.io/

Posts: TBA

Latest Update: 11.05.2020

Credit: this repository is based on awsome works

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Material (Il-Chul Moon, KAIST)

1. Introduction to Artificial Intelligence and Machine Learning I
2. Introduction to Artificial Intelligence and Machine Learning II
3. Artificial Intelligence and Machine Learning (Advanced)

https://kooc.kaist.ac.kr/

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Code (Introduction to Artificial Intelligence and Machine Learning I)

1. MLE: https://zhiyzuo.github.io/MLE-vs-MAP/
2. MAP: https://zhiyzuo.github.io/MLE-vs-MAP/
3. Decision Tree: https://github.com/gilbutITbook/007022/blob/master/code/ch03/ch03.ipynb
4. Naive Bayes Classifier: https://jakevdp.github.io/PythonDataScienceHandbook/05.05-naive-bayes.html
5. Linear Regression: https://github.com/gilbutITbook/007022/blob/master/code/ch10/ch10.ipynb
6. Logistic Regression: https://github.com/Jeiyoon/007022/blob/master/code/ch03/ch03.ipynb
7. Support Vector Machine: https://github.com/Jeiyoon/007022/blob/master/code/ch03/ch03.ipynb
8. Training/Testing and Regularization: https://github.com/Jeiyoon/007022/blob/master/code/ch06/ch06.ipynb

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Code (Introduction to Artificial Intelligence and Machine Learning II)

1. Bayesian Network: https://github.com/pgmpy/pgmpy_notebook/blob/master/notebooks/9.%20Learning%20Bayesian%20Networks%20from%20Data.ipynb
2. K-Means Clustering and Gaussian Mixture Model: TBA
3. Hidden Markov Model: TBA
4. Sampling Based Inference: TBA

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Code (Artificial Intelligence and Machine Learning (Advanced))

1. Dirichlet Process: TBA
2. Gaussian Process: TBA
3. Variational Inference: TBA
4. Artificial Neural Network: TBA