Machine learning works by using algorithms to parse data, learn from it, and then make determinations or predictions. Here’s a simplified explanation of the steps involved: It’s worth noting ...

Machine-learning algorithms find and apply patterns ... a deep neural network—deep because it has many, many layers of simple computational nodes that work together to munch through data and ...

But it's particularly well suited to decisions that require very simple and repetitive tasks at large scale. For example, the US Postal Service has been successfully using machine learning systems ...

The result is a machine learning framework that is easier to work with—for example, by using the relatively simple Keras API for model training—and more performant. Distributed training is ...

Machine learning is a field of study within artificial ... In a way, this mimics simple conditioning, like Pavlov and his ...

Not everything can be told to a computer in a program, which explains why machine learning was invented. It’s simple to teach a computer to calculate, but to teach it to paint a picture or write ...

Machine learning is a subfield of artificial intelligence, which explores how to computationally simulate (or surpass) humanlike intelligence. While some AI techniques (such as expert systems) use ...