The Recentive decision exemplifies the Federal Circuit’s skepticism toward claims that dress up longstanding business problems in machine-learning garb, while the USPTO’s examples confirm that ...

Here’s an unusual concept: a computer-guided mechanical neural network (video, embedded below.) Why would one want a mechanical neural network? It’s essentially a tool to explore what it would take to ...

The goal of a regression problem is to predict a single numeric value, for example, predicting the annual revenue of a new restaurant based on variables such as menu prices, number of tables, location ...

Dr. James McCaffrey of Microsoft Research uses a full-code, step-by-step demo to show how to predict the annual income of a person based on their sex, age, state where they live and political leaning.

The best way to understand neural networks is to build one for yourself. Let's get started with creating and training a neural network in Java. Artificial neural networks are a form of deep learning ...

Modern neural networks, with billions of parameters, are so overparameterized that they can "overfit" even random, structureless data. Yet when trained on datasets with structure, they learn the ...

Researchers are training neural networks to make decisions more like humans would. This science of human decision-making is only just being applied to machine learning, but developing a neural network ...

Deep neural networks can perform wonderful feats thanks to their extremely large and complicated web of parameters. But their complexity is also their curse: The inner workings of neural networks are ...