It aims to summarize and reproduce the textbook "The Elements of Statistical Learning" 2/E by Hastie, Tibshirani, and Friedman
Currently working the early chapters, I try to implement without frameworks like scikit-learn for showing the algorithms that the textbook introduces to me.
Also starting with the neural networks, I decided to use PyTorch which seems less magical (They says that PyTorch Tensor is numpy with GPU support).
Use your favorite virtualenv system and install the below dependencies; quite standard ones.
- numpy
- scipy
- matplotlib
- pandas
- jupyter
- pytorch
(esl) $ pip install ipython numpy scipy matplotlib pandas jupyter
# The command below installs pytorch for Python 3.6 without CUDA support.
# For other settings, consult with pytorch.org.
(esl) $ pip install http://download.pytorch.org/whl/cpu/torch-0.3.1-cp36-cp36m-linux_x86_64.whl
Just run jupyter notebook
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