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1/29/2021
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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 created 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.
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
Calculus
Probability
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)
Publisher: Udemy
Instructor: 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
After Extract, watch with your favorite Player.
English subtitle
Quality: 720p
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