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 Modern Fortran by Milan Curcic
In this part, we’ll conclude the article by using built-in functions and whole-array arithmetic to identify risky stocks, and find good times to buy and sell.
From Spark in Action, 2nd Ed. by Jean Georges Perrin
This is the first in a series of 4 articles on the topic of ingesting data from files with Spark. This section deals with ingesting data from CSV.
Six Questions for Kesha Williams of AWS Machine Learning in Motion
Kesha Williams is a full-stack web developer specializing in Java and AWS. She has won numerous awards for her innovative development, as well as her work as a college professor, speaker, tech blogger, and mentor. The founder of Colors of STEM, which cultivates role models to inspire girls of all races to enter the science and tech fields.
From Deep Learning Crash Course by Oliver Zeigermann
From Graph-Powered Machine Learning by Alessandro Negro
From Deep Learning with JavaScript by Shanqing Cai, Stanley Bileschi, Eric D. Nielsen with Francois Chollet
From our Deep Learning Crash Course by Oliver Zeigermann
From Deep Learning for Search by Tommaso Teofili
This article discusses how neural networks can help generate text that a human might write in order to provide more sensitive suggestions and enhance autocomplete functionality.
By Vladimir Bok, author of GANs in Action
This article discusses the history and meaning of Generative Adversarial Networks, and their potential.