Supervised machine learning is a branch of AI. This article covers the relevant concepts, importance in various fields, practical use in investing, and CAPTCHA applications.

To a large extent, supervised ML is for domains where automated machine learning does not perform well enough. Scientists add supervision to bring the performance up to an acceptable level.

Artificial intelligence (AI) and machine learning (ML) are transforming our world. When it comes to these concepts there are important differences between supervised and unsupervised learning.

In machine learning problems where supervised learning might be a good fit but there’s a lack of quality data available, semi-supervised learning offers a potential solution.

Machine learning is a branch of artificial intelligence that includes algorithms for automatically creating models from data. At a high level, there are four kinds of machine learning: supervised ...

In recent years, machine learning (ML) algorithms have proved themselves to be remarkably useful in helping people deal with different tasks: data classification and clustering, pattern revealing ...

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.

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.

While some AI techniques (such as expert systems) use other approaches, machine learning drives most of the field’s current progress by focusing on one thing: using algorithms to automatically improve ...