Machine Learning Algorithms Articles

Javaid Nabi

Updated on August 27, 2025

Machine learning is an application of artificial intelligence where a machine learns from past experiences (input data) and makes future predictions.

Bayley Wang

Updated on August 25, 2025

While generative AI continues to evolve, robotics remains stuck in the past. Our expert examines what needs to change and how vision-language-action models can help.  

Sam Daley

Updated on August 20, 2025

A subset of artificial intelligence, machine learning lets computers learn new things they haven’t been specifically programmed to do. Here’s how it works, its types, applications and a brief history of machine learning.

Sunny Betz

Updated on August 15, 2025

Artificial intelligence is necessary for optimizing business and solving problems. Here are the top AI tools.

Benyamin Deldar and David Hanbury

Updated on August 13, 2025

Missed medical appointments are a quiet crisis that lead to lost clinical capacity and missed diagnoses. Fortunately, AI can help alleviate the problem.

James Le

Updated on August 12, 2025

A machine learning algorithm is a set of instructions that enables a system to learn patterns from data and make predictions or decisions without being explicitly programmed for each task. Here are the machine learning algorithms beginners should know.

Parag Radke

Updated on August 11, 2025

Forward chaining and backward chaining are two approaches to designing an expert system for AI that help you solve complex problems. Learn how they work.

Gordon Gottsegen

Updated on August 05, 2025

Machine learning is at the helm of social media, self-driving cars and more daily applications.

Artem Oppermann

Updated on July 31, 2025

CatBoost is a machine learning gradient-boosting library that builds decision trees optimized for handling categorical data with high accuracy and minimal data preprocessing.

Sara A. Metwalli

Updated on July 31, 2025

Data labeling is the process of annotating raw data with meaningful tags or classifications so machine learning models can learn to recognize patterns and make accurate predictions.