September 2018
Intermediate to advanced
296 pages
9h 10m
English
Content preview from Python Reinforcement Learning Projects
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AlphaGo
AlphaGo's main innovation is how it combines deep learning and Monte Carlo tree search to play Go. The AlphaGo architecture consists of four neural networks: a small supervised learning policy network, a large supervised-learning policy network, a reinforcement learning policy network, and a value network. We train all four of these networks plus the MCTS tree. The following sections will cover each training step.
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.