MachineLearning

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MachineLearning

★ 18 Open GitHub ↗

Deep learning and machine learning example codes for practice

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# Example codes for Machine Learning Education  (https://github.com/callee2006/MachineLearning)

* colab에서 open, run 방법

1. colab 열기 (colab.research.google.com)
  1. Google account로 로그인
  1. 파일 -> 노트열기 -> GITHUB
  
     GitHub URL에 "https://github.com/callee2006/MachineLearning"
  
  1. 노트 선택 및 실행

(git 설치 후 "git clone https://github.com/callee2006/MachineLearning" 하면 다운로드 받으실 수 있지만, scikit-learn, matplotlib, graphviz, pytorch, mglearn 등이 설치되어 있어야 실행 가능합니다.)

예제코드 목록

* python quickstart examples
    - python_core.ipynb (minimum tutorial)
    - python_tutorial.ipynb (quick tutorial)

* accessing datasets in python
    - dataset.ipynb

* k-nearest neighbor
    - kNN_IRIS.ipynb
 
  * linear and regularized regression (including Ridge, Lasso, Elastic-Net)
    - linear_regression.ipynb

* Decision Tree, Random Forests, XGBoost
    - tree_and_ensemble.ipynb

* Support Vector Machines
    - SVM (scikit-learn).ipynb

* MLP examples - scikit-learn
    - MLP (scikit-learn).ipynb

* MLP examples - pytorch
    - MLP_MNIST.ipynb         # digit image classification
    - MLP_regression.ipynb    # regression using MLP
    - MLP_autoencoder.ipynb   # autoencoder

* CNN example - pytorch
    - CNN_MNIST.ipynb         # CPU and GPU
  
  * RNN (sequence prediction) - pytorcyh
    - sequence_prediction (RNN).ipynb
    - sequence_prediction (LSTM per time).ipynb
    - sequence_prediction (LSTM per seq).ipynb     # CPU and GPU

MachineLearning

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