1Supervised, unsupervised and reinforcement learning
ML covers the methods that allow a program to learn from data.
2Data, the raw material
A model is never better than the data it was trained on.
3Training a first model
Training means adjusting the parameters to minimise errors.
4Evaluating a model
What matters is performance on data the model has never seen.