Machine Learning

Linear Regression Visualizer

Predict the value of a dependent variable based on an independent variable using the Least Squares method and Gradient Descent.

Learning Rate:

Click on the canvas to add custom data points.

y = 0.00x + 0.00

Ready. Add points and click 'Train' to see the line learn.

Adjust the slope (m) and intercept (c) manually to fit the data points and beat the optimal machine loss.

Slope (m): 0.00

Intercept (c): 0

Your Loss (MSE): 0.00

Optimal Loss (MSE): 0.00

0.0000

Goal: Minimize the Mean Squared Error.

1. Start with random m (slope) and c (intercept).

2. Calculate the Loss (difference between line and points).

3. Use Gradient Descent to nudge m and c in the direction that reduces error.