Slideshare
https://www.slideshare.net/ssuser55d0a21/
Gitbook
https://nlp.gitbook.io/book/
목차
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- 01.Machine Learning 개발 환경 세팅하기.ipynb
- 02.JupyterNotebook.ipynb
- 03.kNN(k-Nearest Neighbors).ipynb
- 04.kNN-hand_writing_recognition.ipynb
- 05. Decision Tree Algorism.ipynb
- 06. Decision Tree Algorism Math.ipynb
- 07. Decision Tree - 파이썬으로 의사결정 트리 구현 하기.ipynb
- 08.Naive Bayes - Probability 쉽게 이해하기 .ipynb
- 09.Naive Bayes(1-2) -Bayes' Theorem.ipynb
- 10.Naive Bayes(2-2)-Python.ipynb
- 11.Linear Regression.ipynb
- 12.K-mean Clustering.ipynb
- 13.Overfitting.ipynb
- 14.Overfitting, UnderFitting.ipynb
- 15.Distributions.ipynb
- Machine Learning Boosting_20180424.pdf
ChangWookJun / @changwookjun (changwookjun@gmail.com)