Machine-learning algorithms are responsible for the vast majority of the artificial intelligence advancements and applications you hear about. (For more background, check out our first flowchart ...

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.

List of best Machine Learning Models for time series forecasting, Stock Prediction, Multiclass Classification, Regression, Small Datasets, Big Datasets, etc.

Consider a machine learning model that classifies images. If your dataset is composed of 100×100-pixel images, then your problem space has 10,000 features, one per pixel.

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.

It may be the buzziest tech trend of the moment, but machine learning is no easy matter. Before you jump into writing machine learning algorithms, here are the basics you need to start a project.

The most prominent and common algorithms used in machine learning historically and today come in three groups: linear models ... Machine Learning Basics Newsweek's AI and Data Science in Capital ...

New work from Zhong and others shows that priming a learning model in this way can supercharge learning in simulated environments, both online and in the real world with robots. And it doesn’t just ...

There is one other advantage that the researchers have ensured applies to their algorithm. In many machine-learning systems, the machine creates its own set of variables and an internal model.