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Hyperparameter optimization for machine learning

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Choosing the correct hyperparameters for machine learning or deep learning models is one of the best ways to extract the last juice out of your models. In this article, I will show you some of the best ways to do hyperparameter tuning that are available today.
It is possible and recommended to search the hyper-parameter space for the best cross validation score.

Scientific Area:

Learning, Optimization

Target Group:

Cite as:
Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel, O., ... & Duchesnay, E. (2011). Scikit-learn: Machine learning in Python. the Journal of machine Learning research, 12, 2825-2830.

Author of the review:
Filipe Alves
University of Minho


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Stefano Zampini

Hyperparameter optimization is a fundamental step in building every ML model and GridSearchCV is a function of scikit-learn library which allows you to easily implement it