Advanced Deep Learning & Tensor Tutorial
June 21st, 1pm ANB 105
Basic knowledge of deep learning (convolutions, MLP)
Knowledge of Python
- Deep learning refresher — how to train your deep nets (1:00 - 1:30)
- Tensor methods Quickstart (1:30 - 2:00)
- Short break (2:00 - 2:10)
- Combining tensor methods and deep learning (2:10 - 3:00)
- Short break (3:00 - 3:10)
- Ultimate compression with (binary) quantisation of deep neural networks (3:10 - 3:40)
- Break + setup (3:40 - 4:00)
- Hands-on session + Q&A: (4:00 - 5:00)
- training a neural network for image classification
- Adding in tensor decomposition
- Binarizing/Quantization the network
Hardware and Software Preparation:
You will need a laptop to get the most of the session, with Python (3.7 or higher) installed, along with PyTorch and TensorLy.
You also need to have the jupyter notebook installed.
If you are new to Python or simply want a pain-free experience, I recommend you install the Anaconda distribution. It comes with all you need shipped-in and ready to use!
conda install jupyterlab
For PyTorch, simply follow the instructions. With conda, it should be something like:
conda install pytorch torchvision -c pytorch
Finally, to install TensorLy to get the latest version, you can clone the Github repository. In the command line, run:
git clone https://github.com/tensorly/tensorly
pip install -e .
Or, if you have an issue during installation, you can also use conda:
conda install -c tensorly tensorly