From Graph Databases in Action by Dave Bechberger
In this article, we’ll review what makes a problem a good graph use case. We’ll start by examining a few general categories of problems and discussing why they might make for good graph use case. Finally, we’ll analyze a general framework that we can use to help us decide if our problem is a good graph use case.
From Grokking Deep Learning for Computer Vision by Mohamed Elgendy
In this part, we will delve into image preprocessing for computer vision systems.
From Build Your Career in Data Science by Emily Robinson and Jacqueline Nolis
From Grokking Machine Learning by Luis G. Serrano
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 Grokking Deep Learning for Computer Vision by Mohamed Elgendy
In this part, we will discuss the input images for computer vision systems.
From Grokking Deep Learning for Computer Vision by Mohamed Elgendy
In this article, we’ll zoom in on the interpreting device component (of a computer vision system) to take a look at the pipeline it uses to process and understand images.
Chapters selected by Jeff Smith
From AI as a Service by Peter Elger, Eoin Shanaghy, and Johannes Ahlmann
From Machine Learning for Mortals (Mere and Otherwise) by Hefin I. Rhys
