Machine Learning

A subset of artificial intelligence where computer systems learn from data and improve performance on specific tasks over time without being explicitly programmed for every scenario. Machine learning algorithms identify patterns in training data and use those patterns to make predictions or decisions on new data. Types include supervised learning (learning from labeled examples), unsupervised learning (finding patterns in unlabeled data), and reinforcement learning (learning through trial and error). Applications range from recommendation systems and fraud detection to image recognition and natural language processing. Machine learning powers most modern AI applications, continuously improving as more data becomes available.

Why it matters

Understanding machine learning basics helps you leverage AI tools effectively and identify opportunities for automation. While building ML models requires expertise, using pre-trained models through APIs enables non-technical entrepreneurs to harness powerful capabilities.