Interactive visualizations of machine learning concepts running directly in your browser.
Rewards track balanced timesteps per episode.
Training a model to predict housing prices (Target) based on area (Feature).
Dataset: California Housing (Normalized)
Left: The regression line (red) fitting the data points (blue). As loss decreases, the line aligns better with the data trend.
Linear regression is mathematically identical to a single-neuron neural network (with linear activation).
Watch the weight (w) and bias (b) update in real-time as gradient descent optimizes them, just like in complex deep networks!
Try a high learning rate (> 0.5) to see divergence — the path will oscillate or fly off the landscape.
Green circle = optimal parameters (global minimum). Red = current position. Yellow = descent path.