This repository contains the code for my neural learning/PyTorch lecture. See the lecture notebooks and slides for the lecture content.
.
├── Makefile # run `make help` to see make targets
├── README.md # this readme file
├── requirements.txt # virtualenv requirements file
├── configs # notebook configs
├── docs # sources, e.g., images for notebooks
├── notebook # lecture notebooks
└── src # custom python module
- Python 3.7
virtualenv
Please familiarize yourselves with virtualenv (or a similar tool such as conda). Some background information can be found in the virtualenv docs or here.
In the lecture, we will use Jupyter notebooks to illustrate implementation-related key points. Please make sure that you can execute the notebooks before joining the class so you can easily follow the coding parts in the lectures.
The Makefile included in this repository is purely for convenience (e.g., setting up the virtual environment, launching a notebook server). It should work on Linux and Mac OS X systems.
$ make help
Make targets:
build install dependencies and prepare environment
clean remove *.pyc files and __pycache__ directory
distclean remove virtual environment
run run jupyter lab
format format python code (black and isort)
activate-vim activate vim key bindings for jupyter
deactivate-vim deactivate vim key bindings for jupyter
Check the Makefile for details
- Open a terminal and navigate to the path that you want to clone the repository to
- Clone the repository
$ git clone git@github.com:sbstn-gbl/dl-lecture.git - Navigate to repository path, create virtual environment and install required modules with
$ cd dl-lecture && make build - Start a notebook server with
$ make run
If make does not work on your computer run the steps included in the Makefile manually. You only need to do this setup once.