Advanced AI Deep Reinforcement Learning in Python. The Complete Guide to Mastering Artificial Intelligence using Deep Learning and Neural Networks
This course is all about the application of deep learning and neural networks to reinforcement learning.
If you’ve taken my first reinforcement learning class, then you know that reinforcement learning is on the bleeding edge of what we can do with AI.
Specifically, the combination of deep learning with reinforcement learning has led to AlphaGo beating a world champion in the strategy game Go, it has led to self-driving cars, and it has led to machines that can play video games at a superhuman level.
Reinforcement learning has been around since the 70s but none of this has been possible until now.
Advanced AI Deep Reinforcement Learning in Python Description
Know reinforcement learning basics, MDPs, Dynamic Programming, Monte Carlo, TD Learning
College-level math is helpful
Experience building machine learning models in Python and Numpy
Know how to build ANNs and CNNs using Theano or Tensorflow
What you’ll learn
Build various deep learning agents (including DQN and A3C)
Apply a variety of advanced reinforcement learning algorithms to any problem
Q-Learning with Deep Neural Networks
Policy Gradient Methods with Neural Networks
Reinforcement Learning with RBF Networks
Use Convolutional Neural Networks with Deep Q-Learning
Who this course is for:
- Professionals and students with strong technical backgrounds who wish to learn state-of-the-art AI techniques