Deep Q-Learning Network From Scratch in Python, TensorFlow, and OpenAI Gym - Part 1- Reinforcement

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#reinforcementlearning #machinelearning #deepqlearning #dqn #controlengineering #datascience #controltheory #qlearning #openaigym #openai
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THIS IS THE FIRST PART!

In this reinforcement learning tutorial, we explain the basics of the deep Q learning network reinforcement learning algorithm. We explain how to implement this algorithm in Python by using the TensorFlow library. We perform tests in the OpenAI Gym Cart-Pole environment.
  1. Aleksandar Haber PhD
  2. reinforcement learning
  3. machine learning tutorial
  4. action value function
  5. state transition probability
  6. Markov decision process
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Комментарии
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It takes a significant amount of time and energy to create these free video tutorials. You can support my efforts in this way:
- You Can also press the Thanks YouTube Dollar button

aleksandarhaber
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You are doing awesome work. Thank you for sharing this resource.

PanicGiraffe
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I have no idea how to thank you. I was scared of reinforcement learning and watched a lot of tutorials but these are the ones that actually we into my head. You explained those complex ideas in a less scary way.

nabilanoor
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Thanks for sharing this video with us ❤

aasheesh
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Is it also possible to do this when action space is continuous (without discretizing action space)? Maximizing over the action might be inefficient or is there some trick to do this?

id-icou
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