From 633639d3e77f844badc5913c73458dc868d2d5ad Mon Sep 17 00:00:00 2001 From: Thomas Simonini Date: Sat, 31 Dec 2022 21:11:47 +0100 Subject: [PATCH] Update --- units/en/live1/live1.mdx | 3 +-- units/en/unit3/deep-q-network.mdx | 2 +- 2 files changed, 2 insertions(+), 3 deletions(-) diff --git a/units/en/live1/live1.mdx b/units/en/live1/live1.mdx index 821ad23..f81bca8 100644 --- a/units/en/live1/live1.mdx +++ b/units/en/live1/live1.mdx @@ -1,4 +1,4 @@ -# Live 1: Deep RL Course. Intro, Q&A, and playing with Huggy 🐶 +# Live 1: How the course work, Q&A, and playing with Huggy 🐶 In this first live stream, we explained how the course work (scope, units, challenges, and more) and answered your questions. @@ -6,5 +6,4 @@ And finally, we saw some LunarLander agents you've trained and play with your Hu - To know when the next live is scheduled **check the discord server**. We will also send **you an email**. If you can't participate, don't worry, we record the live sessions. \ No newline at end of file diff --git a/units/en/unit3/deep-q-network.mdx b/units/en/unit3/deep-q-network.mdx index 75c66d3..b69dc58 100644 --- a/units/en/unit3/deep-q-network.mdx +++ b/units/en/unit3/deep-q-network.mdx @@ -30,7 +30,7 @@ No, because one frame is not enough to have a sense of motion! But what if I add Temporal Limitation That’s why, to capture temporal information, we stack four frames together. -Then, the stacked frames are processed by three convolutional layers. These layers **allow us to capture and exploit spatial relationships in images**. But also, because frames are stacked together, **you can exploit some spatial properties across those frames**. +Then, the stacked frames are processed by three convolutional layers. These layers **allow us to capture and exploit spatial relationships in images**. But also, because frames are stacked together, **you can exploit some temporal properties across those frames**. If you don't know what are convolutional layers, don't worry. You can check the [Lesson 4 of this free Deep Reinforcement Learning Course by Udacity](https://www.udacity.com/course/deep-learning-pytorch--ud188)