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A review for research, educational and recommendations

Recommendation in beta release. In analysis state… ⌛


Consider TPOT your Data Science Assistant. TPOT is a Python Automated Machine Learning (AutoML) tool that optimizes machine learning pipelines using genetic programming.

TPOT home

Summary

TPOT (Tree-based Pipeline Optimization Tool) was developed by the University of Pennsylvania and is a Python package that is free to use. Albeit free, the package is extremely powerful and has achieved outstanding performance in various datasets: around 97% accuracy for the Iris dataset, 98% for MNIST digit recognition, and 10 MSE for Boston Housing Prices prediction (1).


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.

(TPOT home).

Tutorials in Github: bit.ly/32TMW5u
Manual: epistasislab.github.io/tpot

Bibliography |Author

(1).- The Death of Data Scientists. . Chin, J. (13/12/2019). towards datas cience. [Recuperado 20/02/2020 de [towardsdatascience.com/the-death-of-data-scientists-c243ae167701)]