Name		Name	Last commit message	Last commit date
parent directory ..
README.md		README.md
T0_ hands_on_preparation.ipynb		T0_ hands_on_preparation.ipynb
T1_fitting_sin_with_MLP.ipynb		T1_fitting_sin_with_MLP.ipynb
T2_binary_classification_with_MLP.ipynb		T2_binary_classification_with_MLP.ipynb
T3_multiclass_classification_with_MLP.ipynb		T3_multiclass_classification_with_MLP.ipynb
T4_CIFAR10_classification_with_CNN.ipynb		T4_CIFAR10_classification_with_CNN.ipynb
T5_Cats_Dogs_classification_with_ResNet.ipynb		T5_Cats_Dogs_classification_with_ResNet.ipynb
utils.py		utils.py

README.md

Tutorials for the Introduction to Machine/Deep Learning course

First, activate the conda environment on your machine:

conda activate eschool2022

Then, install PyTorch (pytorch.org), jupyter and other dependencies

conda install pytorch torchvision torchaudio -c pytorch
conda install plotly
pip install tensorboard
pip install pytorch-lightning

If you have a GPU available on your machine, you may run also:

conda install cudatoolkit=11.3 -c pytorch

Then, run all cells of T0_hands_on_preparation.ipynb

You also need to download the data for tutorial 5: https://zenodo.org/record/5226945#.Yd_3_NvjJpo and unzip the file in './data'