Autoplay
Autocomplete
Previous Lesson
Complete and Continue
Advanced AI: Deep Reinforcement Learning in Python
Introduction and Logistics
Introduction and Outline (7:23)
Special Offer! Get the VIP version of this course (1:14)
Where to get the Code (5:01)
How to Succeed in this Course (5:51)
The Basics of Reinforcement Learning
Reinforcement Learning Section Introduction (6:34)
Elements of a Reinforcement Learning Problem (20:18)
States, Actions, Rewards, Policies (9:24)
Markov Decision Processes (MDPs) (10:07)
The Return (4:56)
Value Functions and the Bellman Equation (9:53)
What does it mean to “learn”? (7:18)
Solving the Bellman Equation with Reinforcement Learning (pt 1) (9:49)
Solving the Bellman Equation with Reinforcement Learning (pt 2) (12:01)
Epsilon-Greedy (6:09)
Q-Learning (14:15)
How to Learn Reinforcement Learning (5:56)
Suggestion Box (3:03)
OpenAI Gym and Basic Reinforcement Learning Techniques
OpenAI Gym Tutorial (5:43)
Random Search (5:48)
Saving a Video (2:18)
CartPole with Bins (Theory) (3:51)
CartPole with Bins (Code) (6:25)
RBF Neural Networks (10:26)
RBF Networks with Mountain Car (Code) (5:28)
RBF Networks with CartPole (Theory) (1:54)
RBF Networks with CartPole (Code) (3:11)
Theano Warmup (3:04)
Tensorflow Warmup (2:25)
Plugging in a Neural Network (3:39)
OpenAI Gym Section Summary (3:28)
TD Lambda
N-Step Methods (3:14)
N-Step in Code (3:40)
TD Lambda (7:36)
TD Lambda in Code (3:00)
TD Lambda Summary (2:21)
Policy Gradients
Policy Gradient Methods (11:38)
Policy Gradient in TensorFlow for CartPole (7:19)
Policy Gradient in Theano for CartPole (4:14)
Continuous Action Spaces (4:16)
Mountain Car Continuous Specifics (4:12)
Mountain Car Continuous Theano (7:31)
Mountain Car Continuous Tensorflow (8:07)
Mountain Car Continuous Tensorflow (v2) (6:11)
Mountain Car Continuous Theano (v2) (7:31)
Policy Gradient Section Summary (1:36)
Deep Q-Learning
Deep Q-Learning Intro (3:52)
Deep Q-Learning Techniques (9:13)
Deep Q-Learning in Tensorflow for CartPole (5:09)
Deep Q-Learning in Theano for CartPole (4:48)
Additional Implementation Details for Atari (5:36)
Deep Q-Learning in Tensorflow for Breakout (5:58)
Deep Q-Learning in Theano for Breakout (6:42)
Partially Observable MDPs (4:52)
Deep Q-Learning Section Summary (4:45)
Course Summary (4:57)
Appendix
What order should I take your courses in? (pt 1) (11:18)
What order should I take your courses in? (pt 2) (16:07)
How to Code by Yourself (part 1) (15:54)
How to Code by Yourself (part 2) (9:23)
How to Succeed in this Course (Long Version) (10:24)
BONUS: Where to get discount coupons and FREE deep learning material (5:31)
Epsilon-Greedy
Lesson content locked
If you're already enrolled,
you'll need to login
.
Enroll in Course to Unlock