Kevin Ferguson, co-author of Deep Learning and the Game of Go, was our latest Data Speaker Series guest. He talked about how AlphaGo Zero combines tree search and reinforcement learning in a novel way.
Six Questions for Kevin Ferguson, co-author of Deep Learning and the Game of Go.
Kevin Ferguson and Max Pumperla are deep learning specialists skilled in distributed systems and data science. Together, they built the open source bot BetaGo. They also both count Max, the hero of the movie Pi, as a major influence. “He’s a talented mathematician who slowly loses his mind over the stock market and has an intense relationship with his power tools. That’s essentially my short bio,” says Pumperla.
From Deep Learning and the Game of Go by Max Pumperla and Kevin Ferguson
This article shows you how to use the minimax algorithm to help your game bot decide its next move.
From Deep Learning and the Game of Go by Max Pumperla and Kevin Ferguson
This article, from Deep Learning and the Game of Go, discusses tree search algorithms and their relevance to various types of games.
From Deep Learning and the Game of Go by Max Pumperla and Kevin Ferguson
This article is an excerpt from chapter 2 of the upcoming MEAP Deep Learning and the Game of Go. We’re going to look at the game of Go and discuss why it’s such a good subject and learning tool for machine learning and deep learning. Plus, we’ll also discover why games in general are such a good subject for AI as well as which aspects of game playing can be solved with machine learning.