Machine learning algorithms form the backbone of intelligent systems, enabling them to learn from data and make accurate predictions or uncover hidden patterns.

Azure Machine Learning has both AutoML, which sweeps through features and algorithms, and hyperparameter tuning, which you typically run on the best algorithm chosen by AutoML.

Discover the fascinating world of machine learning and understand how computers mimic human learning processes to make predictions, recognize patterns, and solve complex problems.

Machine learning may find things that humans would miss; furthermore, the more data that is fed to the algorithms, the better they get at identifying trends and patterns.

AEquity aims to improve training for healthcare machine-learning algorithms by assessing the accuracy and fairness of the data they're fed.

Deep learning vs. machine learning: what's the difference between the two? We provide a simplified explanation of both AI-based technologies.

Computer algorithms are a set of instructions used to calculate and solve a problem. The quality of AI deep learning depends not only on the algorithm but also on the data.

Machine Learning systems, also called models, are trained by humans to use an algorithm to classify and analyze data, make predictions, and take actions of limited complexity.

Set up a supervised learning project, then develop and train your first prediction function using gradient descent in Java.