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ML Template

A sample repo for structuring ML projects

Setting up your local environment (in windows)

  • Make sure to have chocolatey installed
  • Install Docker using choco install docker-desktop
  • Install make using choco install make
  • Have conda/anaconda installed
  • run make env within the root directory of this project to create an empty environment
  • Activate environment with conda activate ml_template
  • install all dependencies by running make deps from the root directory of this project

Making and merging branches

  • run git checkout main, this will get you the main version of the code
  • run git pull origin main, this will grab the latest main version from github.com
  • run git checkout -b <your_name>/<issue_number> to create a new branch
  • Make you changes to the code
  • run git add <file_name> to add say you want to keep the changes
  • run git commit -m "<issue_number> : decription" to create a snapshot of your updated code
  • run git push origin <branch_name> to upload your code to github.com

Running tests

  • Run make tests to run unit test suite in the ./unittests folder using pytest

Using docker as a dev environment

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Sample Machine Learning project template

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