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Learn AI with Python · Lesson

Deep Q-Learning

Using neural networks for reinforcement learning.

1

Deep Q-Learning

Deep Q-Learning is an extension of Q-Learning that uses a neural network to approximate the Q-Table. This allows reinforcement learning to scale to environments with large or continuous state-action spaces.

Deep Q-Learning — illustration 1

2

Why Deep Q-Learning?

Deep Q-Learning addresses the limitations of traditional Q-Learning:

  • Handles high-dimensional state spaces (e.g., images).
  • Avoids the need to store large Q-Tables in memory.
  • Generalizes across states using neural networks.

All lessons in this course

  1. Basic Concepts in Reinforcement Learning
  2. Q-Table Concept
  3. Implementing Q-Table in Python
  4. Deep Q-Learning
  5. Exploring OpenAI Gym
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