Opoca library aims to drastically speed up producing proof of concepts (PoC) for machine learning projects.
Project description
Opoca
Opoca library aims to drastically speed up producing proof of concepts (PoC) for machine learning projects.
We define proof of concept as a small, quick and (not) dirty projects that results in:
- exploratory data analysis
- log of experiments along with models
- deployable best model
- demo (jupyter notebook/streamlit app etc.)
- short report including results analysis
There are several challenges that ML Engineer faces given a task to build new PoC project:
- it's not easy to track and reproduce experiments
- it's not easy to version and share data
- it's not easy to schedule jobs and not burn much money on training
- there's a lot of code that can be reused between different PoCs such as:
- training logic for similar problems
- evaluation logic
- plotting
- hyperparameters search
- generic feature engineering transformations
Those are just few and a list is not complete without a doubt.
Prerequisites
Before you begin, ensure you have met the following requirements:
- You have installed the latest version of poetry
Installing Opoca
Opoca is installable from PyPi by executing:
pip install opoca
One may also use docker to build image:
docker build -t opoca -f Dockerfile .
And run bash session interactively by executing:
docker run -it --rm -v $PWD:/home -w /home opoca bash
Contributing to Opoca
To contribute to Opoca
, follow these steps:
- Fork this repository.
- Create a branch:
git checkout -b <branch_name>
. - Make your changes and commit them:
git commit -m '<commit_message>'
- Push to the original branch:
git push origin <project_name>/<location>
- Create the pull request.
Alternatively see the GitHub documentation on creating a pull request.
Contributors
Thanks to the following people who have contributed to this project:
Contact
If you want to contact me you can reach me at ml-team@netguru.com.
License
This project uses the following license: Apache License, Version 2.0.
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