Full stack deep learning starter kit.
We are using issues to write the documentation. It is advisible to use discussions if you find any errors, new topics etc and keep the issues clean.
Contributions are most welcome
- Use discussions for new topics and errors.
- Donot raise pull requests. Please write a blog by creating an issue and get it approved on discussions page. Once done, I will add it to the updates section on Readme page. Please check the upcoming section below for ideas.
- [26-11-2020] Docker Setup #2 🍮
- [31-11-2020] setup pre-commit hooks #6 🖌️
- [31-11-2020] Development inside a container using vscode #5 🥇
- [27-01-2021] GitLFS #11 ♨️
- [28-03-2021] Protocol buffers #12, Protocol buffers using Python #14 🤯
- [08-06-2021] einops #16 🧑
- [10-07-2021] python-poetry cheatsheet #17 🎆
- [26-07-2021] oh-my-zsh - make ur terminal more useful #15 📽️
- [29-07-2021] pyenv - creating python environments #21 🎃
- setting up docker and vscode for remote container.
- writing pytest.
- Github actions.
- Github CI/CD pipeline.
- setting up DVC or Git-LFS.
- setting up mlflow/wandb.
- writing apis using fastapi.
- quantization/fp16/int8 calibration.
- onnx.
- tensorrt.
- deploying on edge device.
- Deepstream
- nvidia triton server.
- gRPC
- convolution operations.
- self-supervised learning.
- image classification networks.
- vision transformers.