diff --git a/units/en/unit8/conclusion-sf.mdx b/units/en/unit8/conclusion-sf.mdx index ac9893f..34c85df 100644 --- a/units/en/unit8/conclusion-sf.mdx +++ b/units/en/unit8/conclusion-sf.mdx @@ -1,12 +1,12 @@ # Conclusion -That's all for today. Congrats on finishing this Unit and the tutorial! +That's all for today. Congrats on finishing this Unit and the tutorial! ⭐️ -Now that you've successfully trained your Doom agent, why not try deathmatch? But remember, that's a much more complex level than the one you've just trained. **But it's a nice experiment, and I advise you to try it.** +Now that you've successfully trained your Doom agent, why not try deathmatch? Remember, that's a much more complex level than the one you've just trained, **but it's a nice experiment and I advise you to try it.** If you do it, don't hesitate to share your model in the `#rl-i-made-this` channel in our [discord server](https://www.hf.co/join/discord). -This concludes the last unit. But we are not finished yet! 🤗 The following **bonus unit include some of the most interesting, advanced and cutting edge work in Deep Reinforcement Learning**. +This concludes the last unit, but we are not finished yet! 🤗 The following **bonus unit includes some of the most interesting, advanced and cutting edge work in Deep Reinforcement Learning**. See you next time 🔥, diff --git a/units/en/unit8/introduction-sf.mdx b/units/en/unit8/introduction-sf.mdx index 486b416..9250cf4 100644 --- a/units/en/unit8/introduction-sf.mdx +++ b/units/en/unit8/introduction-sf.mdx @@ -4,7 +4,7 @@ In this second part of Unit 8, we'll get deeper into PPO optimization by using [Sample-Factory](https://samplefactory.dev/), an **asynchronous implementation of the PPO algorithm**, to train our agent playing [vizdoom](https://vizdoom.cs.put.edu.pl/) (an open source version of Doom). -During the notebook, **you'll train your agent to play Health Gathering level**, where our agent must collect health packs to avoid dying. And after that, you can **train your agent to play more complex versions of the levels, such as Deathmatch**. +In the notebook, **you'll train your agent to play the Health Gathering level**, where the agent must collect health packs to avoid dying. After that, you can **train your agent to play more complex levels, such as Deathmatch**. Environment diff --git a/units/en/unit8/introduction.mdx b/units/en/unit8/introduction.mdx index 7657ec1..6e8645d 100644 --- a/units/en/unit8/introduction.mdx +++ b/units/en/unit8/introduction.mdx @@ -17,7 +17,7 @@ This Unit is in two parts:
Environment -
This is the environments you're going to use to train your agents: VizDoom environments
+
These are the environments you're going to use to train your agents: VizDoom environments
Sounds exciting? Let's get started! 🚀