Machine Learning

Machine learning is a branch of artificial intelligence where systems improve their performance on tasks by learning from data rather than following explicitly programmed rules. Instead of writing code that specifies every decision, developers provide training data and an algorithm that identifies patterns, then the resulting model makes predictions or classifications on new, unseen inputs.

The field encompasses several approaches: supervised learning trains on labeled examples to predict outcomes, unsupervised learning finds hidden patterns in unlabeled data, and reinforcement learning optimizes decisions through trial and reward. Practical applications in web development include recommendation engines, spam filtering, image recognition, natural language processing, fraud detection, and predictive analytics. Libraries like TensorFlow, PyTorch, and scikit-learn provide the tools, while cloud APIs from providers like Google, AWS, and OpenAI make it possible to integrate ML capabilities into web applications without training models from scratch. Understanding the basics helps developers evaluate when ML is the right solution and how to work effectively with data science teams.