Machine learning is the engine behind modern artificial intelligence. Rather than programming explicit rules, ML algorithms discover patterns in data — adjusting millions of parameters to minimize error, partition feature spaces, or find hidden structure. The field spans supervised learning (labeled examples), unsupervised learning (discovering clusters), and the deep learning revolution that powers language models, image recognition, and autonomous systems.
These simulations let you see ML algorithms at work. Watch gradient descent navigate a loss landscape. Build a neural network and observe activation propagation. Grow a decision tree that splits data into pure regions. Cluster points with k-means. Explore overfitting — the central tension of machine learning — by adjusting model complexity against training data.