Machine Learning

The mandatory throughline of this roadmap.

• Machine Learning(15 concepts)

  • What Machine Learning Actually Is
  • Data, Features, and Labels
  • Training — Learning as Optimization
  • Generalization and Overfitting
  • Regression — Predicting Numbers
  • Classification — Predicting Categories
  • Trees, Forests, and Ensembles
  • Unsupervised Learning — Finding Structure
  • Evaluating Models — Beyond Accuracy
  • Neural Networks — Stacked Simple Decisions
  • How Networks Train — Backpropagation Intuition
  • Architectures — Encoding Assumptions
  • Transformers and Foundation Models
  • Classical vs Deep — When to Use What
  • What ML Can and Can't Do