CS_ALearn/deep-rl-class
1
0
Fork 0
mirror of https://github.com/huggingface/deep-rl-class.git synced 2026-07-17 03:50:56 +08:00
Code Issues Projects Releases Wiki Activity

Add conclusion

Browse Source
This commit is contained in:
simoninithomas
2023-01-02 21:52:41 +01:00
parent 7bb90190c7
commit c0c4f9b565
1 changed files with 9 additions and 12 deletions
Download Patch File Download Diff File Expand all files Collapse all files

21
units/en/unit4/conclusion.mdx
View File

@@ -1,20 +1,17 @@
# Conclusion
Congrats on finishing this chapter! There was a lot of information. And congrats on finishing the tutorial. You’ve just coded your first Deep Reinforcement Learning agent from scratch using PyTorch and shared it on the Hub 🥳.
**Congrats on finishing this unit**! There was a lot of information.
And congrats on finishing the tutorial. You've just coded your first Deep Reinforcement Learning agent from scratch using PyTorch and shared it on the Hub 🥳.
It's **normal if you still feel confused** with all these elements. **This was the same for me and for all people who studied RL.**
Don't hesitate to iterate on this unit **by improving the implementation for more complex environments** (for instance, what about changing the network to a Convolutional Neural Network to handle
frames as observation)?
Take time to really grasp the material before continuing.
In the next unit, **we're going to learn more about Unity MLAgents**, by training agents in Unity environments. This way, you will be ready to participate in the **AI vs AI challenges where you'll train your agents
to compete against other agents in a snowball fight and a soccer game.**
Don't hesitate to train your agent in other environments. The **best way to learn is to try things on your own!**
Sounds fun? See you next time!
We published additional readings in the syllabus if you want to go deeper 👉 **[https://github.com/huggingface/deep-rl-class/blob/main/unit5/README.md](https://github.com/huggingface/deep-rl-class/blob/main/unit5/README.md)**
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)
In the next unit, we’re going to learn about a combination of Policy-Based and value-based methods called Actor Critic Methods.
And don't forget to share with your friends who want to learn 🤗!
Finally, we want **to improve and update the course iteratively with your feedback**. If you have some, please fill this form 👉 **[https://forms.gle/3HgA7bEHwAmmLfwh9](https://forms.gle/3HgA7bEHwAmmLfwh9)**
### **Keep learning, stay awesome 🤗,**
### Keep Learning, stay awesome 🤗