Interactive ML Tools

Explore the fundamental algorithms behind modern machine learning through interactive visualizations. No installation is needed; the simulations run in your browser after the page assets load.

Think of machine learning like teaching a child to recognize cats. You show them pictures, they guess, you correct them, and they get better over time. These six simplified simulations let you explore how that learning happens inside a computer — the math, the steps, and the feedback loop — all with sliders and buttons you can play with. No coding required.

Neural Network Explorer

Visualize a 2-layer neural network in real time. Adjust weights, change activation functions (ReLU, Sigmoid, Tanh), and watch the forward pass propagate through every neuron.

Neural Networks Forward Pass Activations

Gradient Descent Lab

Watch gradient descent find minima on a loss surface. Click to set starting points, adjust learning rate, and see each optimization step with gradient arrows.

Optimization Gradients Learning Rate

Backpropagation Visualizer

Step-by-step walk through forward and backward propagation in a 2→2→1 network. See every gradient computed via the chain rule with full mathematical derivation.

Backpropagation Chain Rule Gradients

Activation Functions Explorer

Plot ReLU, Leaky ReLU, Sigmoid, Tanh, GELU, SiLU, ELU and Softplus — with their derivatives — and see why the slope of an activation decides whether learning continues.

Activations Derivatives ReLU

K-Means Clustering Playground

Add points, choose k, and step through assignment and centroid updates. Watch the SSE (inertia) shrink as clusters converge — no labels required.

Clustering Unsupervised SSE

Decision Tree Explorer

Grow a CART-style tree one split at a time on two-class data. compare Gini impurity, classification errors and overfitting at different depths.

Classification Gini Impurity Trees

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