Machine learning uses algorithms to turn a data set into a model that can identify patterns or make predictions from new data. Which algorithm works best depends on the problem.

The method informs the machine learning model with a relatively simple process -- correlation through time, the spatial connections between streams, and energy budget equations.

In supervised learning, a set of input variables, such as blood metabolite or gene expression levels, are used to predict a quantitative response variable like hormone level or a qualitative one ...

In this online data science specialization, you will apply machine learning algorithms to real-world data, learn when to use which model and why, and improve the performance of your models. Beginning ...

Before we dive in, recall that machine learning is a class of methods for automatically creating predictive models from data. Machine learning algorithms are the engines of machine learning ...

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.