Learning in Python Cutting-Edge AI: Deep Reinforcement Learning in Python is an educational title published on the Udemy site that deals with Reinforcement Learning and Deep Learning (Neural Networks). With the science of Deep Reinforcement Learning, robots can be produced that have defeated even the most professional chess players in the world. Deep Reinforcement Learning is also used to build artificial intelligence for games such as DOTA 2 and CS: GO. These are just a few of the endless Deep Reinforcement Learning abilities.
We have seen real-world robots learn how to walk and improve even after being trained using simulation. One of the good aspects of simulation is that it does not require expensive real hardware. During this enjoyable course, you will learn many examples of artificial intelligence.
Cutting-Edge AI Features: Deep Reinforcement Learning in Python:
Learn a new application of the A2C algorithm, OpenAI Baselines
Learning and Applying Evolution Strategies (ES)
Learning and Applying DDPG (Deep Deterministic Policy Gradient)
It is best to be familiar with the following before starting this course
- Object-oriented programming
- Python coding: if / else, loops, lists, dicts, sets
- Numpy coding: matrix and vector operations
- Linear regression
- Gradient descent
- Know how to build a convolutional neural network (CNN) in TensorFlow
- Markov Decision Proccesses (MDPs)
Teacher: Lazy Programmer Inc .
Number of lessons: 50 lessons in 9 sections
Duration: 8 hours and 32 minutes
- Know the basics of MDPs (Markov Decision Processes) and Reinforcement Learning
Helpful to have seen my first two Reinforcement Learning courses
Know how to build a convolutional neural network in Tensorflow
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