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Dylan Wilson
2023-04-19 12:11:18 -05:00
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units/en/unitbonus2/hands-on.mdx
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# Hands-on [[hands-on]]
Now that you've learned to use Optuna, we give you some ideas to apply what you've learned:
Now that you've learned to use Optuna, here are some ideas to apply what you've learned:
1️⃣ **Beat your LunarLander-v2 agent results**, by using Optuna to find a better set of hyperparameters. You can also try with another environment, such as MountainCar-v0 and CartPole-v1.
2️⃣ **Beat your SpaceInvaders agent results**.
By doing that, you're going to see how Optuna is valuable and powerful in training better agents,
By doing this, you'll see how valuable and powerful Optuna can be in training better agents.
Have fun,
Have fun!
Finally, we would love **to hear what you think of the course and how we can improve it**. If you have some feedback then, please 👉 [fill this form](https://forms.gle/BzKXWzLAGZESGNaE9)
Finally, we would love **to hear what you think of the course and how we can improve it**. If you have some feedback then please 👉 [fill out this form](https://forms.gle/BzKXWzLAGZESGNaE9)
### Keep Learning, stay awesome 🤗

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units/en/unitbonus2/introduction.mdx
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# Introduction [[introduction]]
One of the most critical task in Deep Reinforcement Learning is to **find a good set of training hyperparameters**.
One of the most critical tasks in Deep Reinforcement Learning is to **find a good set of training hyperparameters**.
<img src="https://raw.githubusercontent.com/optuna/optuna/master/docs/image/optuna-logo.png" alt="Optuna Logo"/>