Based on a lightning talk given at GopherCon 2017 “Building an ML-Powered Game AI using TensorFlow in Go” Video / Slides (Author: Pete Garcin, Developer Advocate @ ActiveState, @rawktron on Twitter and @peteg on Gophers Slack) For GopherCon, we wanted to demonstrate some of the capabilities of the emerging machine learning and data science ecosystem in Go. Originally built as a demo for PyCon, I had put together a simple arcade space shooter game that features enemies powered by machine learning.
A step-by-step guide to building a distributed facial recognition system with Pachyderm and Machine Box.
(Author: Chewxy, @chewxy on Twitter and Gophers Slack) Welcome to the first part of many about writing deep learning algorithms in Go. The goal of this series is to go from having no knowledge at all to implementing some of the latest developments in this area. Deep learning is not new. In fact the idea of deep learning was spawned in the early 1980s. What’s changed since then is our computers - they have gotten much much more powerful.
GopherData is here! Get involved and explore.