Machine Learning (ML)

Executive Definition: Machine Learning (ML) — A field of artificial intelligence that uses algorithms and statistical models to enable computer systems to learn from data.

Unlike traditional software engineering where logic is explicitly programmed, machine learning allows a system to infer rules and relationships from large datasets. By iteratively training on historical data, ML models improve their performance over time and can make accurate predictions or decisions when exposed to new, unseen inputs.

Frequently Asked Questions

What is the difference between supervised and unsupervised learning?

Supervised learning uses labeled data (inputs mapped to known outputs) to train models. Unsupervised learning uses unlabeled data to discover hidden patterns, such as clustering customers by behavior.

Is deep learning the same as machine learning?

Deep learning is a specific subfield of machine learning that uses multi-layered artificial neural networks. All deep learning is machine learning, but ML also includes simpler algorithms like linear regression and random forests.

What is reinforcement learning?

A type of machine learning where an agent learns to make decisions by performing actions in an environment to maximize a cumulative reward, commonly used in robotics and game AI.