Machine learning foundations Learn from examples, prevent data leakage and evaluate predictions.
A path from examples to evaluation
Three free lessons with inspectable exercises. Fit a line, repair a dataset split and choose a classification threshold. No programming background required.
0 / 3 exercises passed- 01
Features, targets and learning from examples
Define a prediction task, fit a small model and use it on a new input.
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Training, validation, test sets and data leakage
Separate fitting from model selection and check whether related examples cross the split.
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Evaluation metrics, baselines and class imbalance
Count classification errors, compare a simple baseline and choose a threshold for a stated goal.
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