A Python package for fast exploration of machine learning pipelines

ATOM is an open-source, easy-to-use machine learning package for Python, capable of running experiments quickly and efficiently, enabling the user to go from raw data to generating insights in just a few lines of code.

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Why you should use ATOM

  • Avoid endless imports and documentation lookups
  • Predefined data cleaning and feature engineering steps
  • 30+ classification and regression models to choose from
  • Possibility to run multiple models with one line of code
  • Fast implementation of hyperparameter tuning
  • Easy way to compare the results from different models
  • 35 plots to analyze the data and model performance
  • Avoid refactoring to test new pipelines

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ATOM: A Python package for fast exploration of machine learning pipelines

During the exploration phase of a project, a data scientist tries to find the optimal pipeline for his specific use case. This usually involves applying standard data cleaning steps, creating or selecting useful features, trying out different models, etc. Testing multiple pipelines requires many lines of code, and writing it all in the same notebook...

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How to test multiple machine learning pipelines with just a few lines of Python

Since it's nearly impossible to know beforehand which transformations will benefit the model's outcome the most, this process usually involves trying out different approaches. For example, if we are dealing with an imbalanced dataset, should we oversample the minority class or undersample the majority...

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From raw data to web app deployment with ATOM and Streamlit

Coming soon...