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Tree-based Pipeline Optimization Tool (TPOT)

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Consider TPOT your Data Science Assistant. TPOT is a Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.TPOT will automate the most tedious part of machine learning by intelligently exploring thousands of possible pipelines to find the best one for your data. Once TPOT is finished searching (or you get tired of waiting), it provides you with the Python code for the best pipeline it found so you can tinker with the pipeline from there. TPOT is built on top of scikit-learn, so all of the code it generates should look familiar… if you’re familiar with scikit-learn, anyway.

 

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Software | AutoML | Technology: Tools, Hardware, and Software

Xcessiv

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Xcessiv is an open-source, web-based application developed using Python and Javascript for automating and visualizing the model selection process, hyperparameter tuning, and feature extraction in machine learning. It provides a user-friendly interface for managing and executing experiments across multiple algorithms and datasets. Xcessiv employs models from the Scikit-learn package, supports parallel hyperparameter searches using Bayesian optimization, and enables easy management and comparison of hundreds of different model-hyperparameter combinations, easy stack ensemble creation, and automated ensemble construction. It can also export created stacked ensembles as a standalone Python file to support multiple levels of stacking.

Link: https://xcessiv.readthedocs.io/en/stable/

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