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Part I

ML Foundations

6 chapters, from the first idea to the working mechanism.

  1. III-01What Machine Learning Actually LearnsExplore →
  2. III-02Samples, Features, Labels and TargetsExplore →
  3. III-03Learning ProblemsExplore →
  4. III-04Training, Validation, Testing and GeneralizationExplore →
  5. III-05Parameters, Hyperparameters, Loss and OptimizationExplore →
  6. III-06Underfitting, Overfitting, Bias, Variance and BaselinesExplore →