Create Unit 1 Bonus

unit1-bonus/readme.md

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+# Unit 1: Bonus 🎁
+- Our teammate @Chris Emezue published a new leaderboard where you can compare your trained agents in new environments 👉  https://huggingface.co/spaces/chrisjay/Deep-Reinforcement-Learning-Leaderboard
+
+## Try new environments 🎮
+Now that you've played with LunarLander-v2 Why not try these environments? 🔥:
+- 🗻 MountainCar-v0  https://www.gymlibrary.ml/environments/classic_control/mountain_car/
+- 🏎️ CarRacing-v1 https://www.gymlibrary.ml/environments/box2d/car_racing/
+- 🥶 FrozenLake-v1 https://www.gymlibrary.ml/environments/toy_text/frozen_lake/
+ 
+## A piece of advice 🧐
+The first Unit, is a very interesting one but also **a very complex one  because it's where you learn the fundamentals.**
+
+That’s normal if you **still feel confused with all these elements**. This was the same for me and for all people who studied RL.
+
+Take time to really grasp the material before continuing. It’s important to master these elements and having a solid foundations before entering the fun part.
+
+We published additional readings in the syllabus if you want to go deeper 👉 https://github.com/huggingface/deep-rl-class/blob/main/unit1/README.md
+
+The hands-on for the first Unit are more funny experiments, but as we'll go deeper, **you'll understand better how to choose the hyperparameters and what model to use. For now, have fun, try stuff you can't break the simulations  🚀 **
+
+### Keep learning, stay awesome.