Practical AI with Python and Reinforcement Learning
Practical AI with Python and Reinforcement Learning
Learn how to use Reinforcement Learning techniques to create practical Artificial Intelligence programs!
Created by Jose Portilla | 20.5 hours on-demand video course
This is the ultimate course online for learning how to use Python to harness the power of Neural Networks to create Artificially Intelligent agents! This course focuses on a practical approach that puts you in the driver’s seat to actually build and create intelligent agents, instead of just showing you small toy examples like many other online courses. Here we focus on giving you the power to apply artificial intelligence to your own problems, environments, and situations, not just those included in a niche library!
What you’ll learn
- Reinforcement Learning with Python
- Creating Artificial Neural Networks with TensorFlow
- Using TensorFlow to create Convolution Neural Networks for Images
- Using OpenAI to work with built-in game environments
- Using OpenAI to create your own environments for any problem
- Create Artificially Intelligent Agents
- Tabular Q-Learning
- State–action–reward–state–action (SARSA)
- Deep Q-Learning (DQN)
- DQN using Convolutional Neural Networks
- Cross Entropy Method for Reinforcement Learning
- Double DQN
- Dueling DQN
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