TensorFlow, Spark MLlib, Scikit-learn, PyTorch, MXNet, and Keras shine for building and training machine learning and deep learning models. Topics Spotlight: New Thinking about Cloud Computing ...

Deep learning allows computational models that are composed of multiple processing layers to learn representations of data with multiple levels of abstraction. These methods have dramatically ...

To use categorical data for machine classification, you need to encode the text labels into another form. There are two common encodings. One is label encoding , which means that each text label ...

Machine-learning algorithms use statistics to find patterns in massive* amounts of data. And data, here, encompasses a lot of things—numbers, words, images, clicks, what have you.

To clear things up, I drew you this flowchart on the back of an envelope so you can work out whether something is using AI or not. This originally appeared in our AI newsletter The Algorithm.