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Introduction

One of the most critical tasks in Deep Reinforcement Learning is to find a good set of training hyperparameters.

Optuna is a library that helps you to automate the search. In this Unit, we’ll study a little bit of the theory behind automatic hyperparameter tuning. We’ll first try to optimize the parameters of the DQN studied in the last unit manually. We’ll then learn how to automate the search using Optuna.

Update on GitHub