What is Machine Learning (ML)?

Machine Learning (ML) is a subset of AI that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. While traditional programming relies on hard-coded rules (If 'X' happens, then do 'Y'), Machine Learning uses statistical models to find patterns. Imagine teaching a child to recognize a 'chair.' You don't give them a list of measurements; you show them many different chairs. Eventually, the child's brain identifies the common patterns of a chair. ML works the exact same way with data.

The process starts with 'training data.' This data could be images, text, or spreadsheets of numbers. By processing this data through an algorithm, the ML system creates a 'model.' This model is essentially a complex mathematical function that can take new, unseen data and make a prediction or decision. The 'learning' part happens as the system minimizes error. If a prediction is wrong, the algorithm adjusts the internal weights of its model to get closer to the correct answer next time. This iterative process is what allows ML to master tasks as varied as language translation and medical diagnosis.