diff --git a/docs/index.html b/docs/index.html index f271038..c967c89 100644 --- a/docs/index.html +++ b/docs/index.html @@ -1,513 +1,553 @@ - - - - - - - - - - - - - - Deep Reinforcement Learning Course - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + Deep Reinforcement Learning Course + + + + + + + + + + + + + + + + + + + + + + + - -
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A Free course in Deep Reinforcement Learning from beginner to expert.

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A Free course in Deep Reinforcement Learning from beginner to expert.

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Some of the agents you'll implement during this course:

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- Deep Reinforcement Learning Course with Tensorflow +
+ Deep Reinforcement Learning Course with Tensorflow -
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This course is a series of articles and videos where you'll master the skills and architectures you need, to - become a deep reinforcement learning expert. -

- You'll build a strong professional portfolio by implementing awesome agents with Tensorflow that - learns to play Space invaders, Doom, Sonic the hedgehog and more! -

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This course is a series of articles and videos where you'll master the skills and architectures you need, + to + become a deep reinforcement learning expert. +

+ You'll build a strong professional portfolio by implementing awesome agents with Tensorflow that + learns to play Space invaders, Doom, Sonic the hedgehog and more! +

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Step 1: What is Deep Reinforcement Learning?

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Step 1: What is Deep Reinforcement Learning?

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You'll learn all the essentials concepts you need to master before diving on the Deep Reinforcement Learning algorithms. -

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  • What’s Deep Reinforcement Learning and what is its process?
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  • Why rewards is the central idea in RL?
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  • What’s the 3 approaches of Reinforcement Learning?
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📚 More ressources:

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You'll learn all the essentials concepts you need to master before diving on the Deep Reinforcement + Learning algorithms. +

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  • What’s Deep Reinforcement Learning and what is its process?
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  • Why rewards is the central idea in RL?
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  • What’s the 3 approaches of Reinforcement Learning?
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📚 More resources:

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Step 2: Q-Learning

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📜 Course:

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You'll learn the Q-learning algorithm and how to implement it with Numpy.

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Step 2: Q-Learning

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📜 Course:

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You'll learn the Q-learning algorithm and how to implement it with Numpy.

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👨‍💻 Create an Agent that learns to play FrozenLake

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👨‍💻 Create an Agent that learns to play FrozenLake

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You'll learn how to implement the Q-learning algorithm with Numpy.

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👨‍💻 Create an Agent that learns to play Taxi-v2

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You'll learn how to implement the Q-learning algorithm with Numpy.

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👨‍💻 Create an Agent that learns to play Taxi-v2

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📚 More resources:

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Step 3: Deep Q-Learning

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📜 Course:

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You'll learn the Deep Q Learning algorithm and how to implement it with Tensorflow.

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Step 3: Deep Q-Learning

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📜 Course:

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You'll learn the Deep Q Learning algorithm and how to implement it with Tensorflow.

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👨‍💻 An Agent that plays Doom and kill enemies

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👨‍💻 An Agent that plays Doom and kill enemies

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👨‍💻 Create an Agent that learns to play Atari Space Invaders

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👨‍💻 Create an Agent that learns to play Atari Space Invaders

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Step 3+: Improvements in Deep Q Learning

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📜 Course:

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You'll learn the latests improvments in Deep Q Learning (Dueling Double DQN, Prioritized Experience Replay and fixed q-targets) and how to implement them with Tensorflow.

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Step 3+: Improvements in Deep Q Learning

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📜 Course:

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You'll learn the latests improvements in Deep Q Learning (Dueling Double DQN, Prioritized Experience + Replay and fixed q-targets) and how to implement them with Tensorflow.

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📹 Video:

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You'll learn the latests improvements in Deep Q Learning (Dueling Double DQN, Prioritized Experience Replay and fixed q-targets) and how to implement them with Tensorflow.

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👨‍💻 Create an Agent that learns to play Doom Deadly corridor

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You'll learn the latests improvements in Deep Q Learning (Dueling Double DQN, Prioritized Experience + Replay and fixed q-targets) and how to implement them with Tensorflow.

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👨‍💻 Create an Agent that learns to play Doom Deadly corridor

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Part 4: Policy Gradients

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In this article you'll learn about Policy gradients and how to implement it with Tensorflow.

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Part 4: Policy Gradients

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In this article you'll learn about Policy gradients and how to implement it with Tensorflow.

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👨‍💻 An Agent that learns to survive in an hostile environment in Doom

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👨‍💻 An Agent that learns to survive in an hostile environment in Doom

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👨‍💻 Create an Agent that learns to play Doom deathmatch

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👨‍💻 Create an Agent that learns to play Doom deathmatch

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Part 5: Advantage Actor Critic (A2C) and Asynchronous Advantage Actor Critic (A3C)

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You'll learn the Actor Critic's logic and how to implement an A2C agent that plays Sonic the Hedgehog with Tensorflow.

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Part 5: Advantage Actor Critic (A2C) and Asynchronous Advantage Actor Critic (A3C)

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You'll learn the Actor Critic's logic and how to implement an A2C agent that plays Sonic the Hedgehog + with Tensorflow.

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👨‍💻 Create an Agent that learns to play Sonic the Hedgehog

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Part 6: Proximal Policy Gradients in A2C style

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You'll learn PPO how to implement it with Tensorflow.

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Part 6: Proximal Policy Gradients in A2C style

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You'll learn PPO how to implement it with Tensorflow.

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-Sonic the Hedgehog 3

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Part 7: Curiosity Driven Learning

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📅 September

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TBA

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How to help?


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3 ways:

👏 and 👍

Clap our articles and like our videos a lot

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Clapping in Medium means that you really like our articles. And the more claps we have, the more our article is shared

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Clapping in Medium means that you really like our articles. And the more claps we have, the more our + article is shared

Liking our videos help them to be much more visible to the deep learning community

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Share and speak about our articles and videos

By sharing our articles and videos you help us to spread the word.

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👨‍💻

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Publish your own implementations.

Show us what you've learned!

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Keep in touch!


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Keep in touch!

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