Machine Learning

Machine Learning (ML) is a subset of artificial intelligence where algorithms learn patterns from data to make predictions or decisions without explicit programming. Instead of writing rules, you provide examples and the algorithm discovers the rules itself.

ML encompasses several approaches: supervised learning (labeled training data), unsupervised learning (finding patterns in unlabeled data), reinforcement learning (learning from rewards/penalties), and semi-supervised learning (combination). Applications include recommendation systems, fraud detection, natural language processing, and computer vision.

The ML workflow involves: data collection, preprocessing, feature engineering, model selection, training, evaluation, and deployment. Modern ML frameworks (PyTorch, TensorFlow, scikit-learn) and cloud services (AWS SageMaker, Google Vertex AI) have made ML more accessible.