tinocalamia / standarized_ml

Repository and resources for standardizing machine learning lifecycles

Standardized ML

Welcome to the Standardized ML Repository!

We believe that a standardization of machine learning projects will lead to increased efficiency, higher model performance, and less time to go to production. By following the guidelines in this repository, you'll be able to reduce the risk of errors, inconsistencies and misunderstandings in your projects.

We encourage you to use this repository as a resource when planning and executing your machine learning projects. Feel free to submit pull requests if you have any improvements or suggestions to share with the community.

This repository is dedicated to providing information and explanations about best practices for structuring machine learning projects. It will contain information on the various stages of the lifecycle such as data collection, preprocessing, model development, testing, and deployment. The goal of this repository is to provide a resource for organizations and individuals looking to standardize their machine learning projects.

Thank you for visiting and happy coding!