189 Hyperparameter Tuning For Dropout

Code generated in the video can be downloaded from here: https://github.com/bnsreenu/python_for_microscopists.

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In this video you will learn about

In this video we quickly go through the concept of

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Crissman Loomis, an Engineer at Preferred Networks, explains how Optuna helps simplify and optimize the process of

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Hyperparameter tuning

Configuring parameters such as batch size, learning rate, number of epochs, model complexity,

Optimization of many deep learning

KerasTuner is an easy-to-use, scalable hyperparameter optimization framework that solves the pain points of hyperparameter ...