ML research

This repository is the machine learning codebase as described in the following guide, which contains good practices for a machine learning researcher to structure day-to-day work.

Quick start

• Clone the repo and create a conda environment by running: conda env create.
• Run training with python run_training.py --config experiments/cifar.yml. This will download CIFAR10 data in a new folder ./cifar10/dataset and save the experiment outputs in ./cifar10/experiments/.

For a new project, create a new trainer class in the trainers folder and implement the abstract methods of the general Trainer class. See trainers/trainer_cifar.py for a detailed example.