← Machine learning basics
Lesson 2 of 4
Regression basics
Watch, read the card, then practise. Linear regression · MAE, MSE and RMSE
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Meanwhile, the notes below and the 60-second cards cover the same ideas.
Practise this topicLinear regression
Linear regression fits a straight line: prediction = weight × feature + bias.
Remember: One feature: y = m·x + c. More features: one weight each.
MAE, MSE and RMSE
MAE, MSE and RMSE measure how far predictions are from the real numbers.
Remember: Lower is better for all three.
Try the example in Code Lab
w, b = 5.0, 40.0 # marks = 5 × hours + 40 hours = 6 print(w * hours + b)