Skip to content

jaks19/Pytorch-Deep-Learning

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

2 Commits
 
 
 
 
 
 
 
 

Repository files navigation

Pytorch-Deep-Learning

About

This repo contains boilerplate code interleaved with tutorials to get ML algorithms running using the PyTorch framework Every file is a jupyter notebook so one needs to install jupyter through conda or pip and use command jupyter notebook in the repo folder to interact with the tutorials and run the code.

Contents

Intro Pytorch.ipynb - Necessary functionality and patterns in PyTorch to get a new PyTorch user who knows ML going fast

Basic NN.ipynb - Skeleton of a PyTorch Neural Net Architecture and boiler-plate code that cbe edited into any required Neural Net

Install Instructions for Jupyter

If you are using pip:

cd introdeeplearning;
pip install virtualenv;
virtualenv pytorchy;
source pytorchy/bin/activate;
pip install --upgrade pip;
pip install tensorflow;
pip install matplotlib;
pip install pandas;
pip install jupyter;
python -m ipykernel install --user --name=pytorchy
echo 'done';
jupyter notebook

From within jupyter, in the top-right corner, select the kernel named "pytorchy" to activate your virtual env

Or if you are using Conda:

git clone https://github.com/jaks19/Pytorch-Deep-Learning.git;
cd introdeeplearning;
conda create -n pytorchy;
source activate pytorchy;
conda install -c conda-forge tensorflow;
pip install matplotlib;
pip install pandas;
conda install jupyter;
echo 'done';
jupyter notebook

About

Implementations of Machine Learning Algorithms in PyTorch

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published