As per Wikipedia, Price Elasticity of Demand (PED or ED or PE) is a measure used in economics to show the responsiveness, or change, of the quantity demanded of a good or...
We first provide a mini-tutorial on Adjoint Algorithmic Differentiation (AAD) (also known as back-propagation in machine learning). We then illustrate how neural netw...
By Rob Farber Now is a great time to be procuring systems as vendors are finally addressing the memory bandwidth bottleneck. Succinctly, memory performance dominates the ...
There’s no doubt about it, probability and statistics is an enormous field, encompassing topics from the familiar (like the average) to the complex (regression anal...
It’s a fact that we cannot live without our smartphones in the globalized world. Mobile has transformed the way we work and live. We do multiple things via our smartpho...
Did you ever wonder why linear regression plays an important role in statistics and machine learning? It is witnessed that linear regression is one of the most commonly a...
We live in a world driven by insights and decision making fueled by data and analytics. Information and technologies are so ubiquitous that no organization needs to be a...
By Dan Howarth and Ajit Jaokar, October 2019. 58 pages. CNN stands for Convolutional Neural Networks. Part 1 will introduce the core concepts of Deep Learning. We will al...
What is RPA? Robotic Process Automation (RPA) is the utilization of programming with machine learning and AI capacities to deal with high-volume, repeatable tasks, and tr...
Introduction Will china dominate AI? When I spoke at the UK China business forum last month, I discussed this topic in response to an audience question. In the current cl...