Why this phase matters

You can get 80% of results by training a model.

You get the next 15–20% by:

• choosing the right validation strategy
• tuning hyperparameters
• building consistent preprocessing pipelines

Phase 7 topics

1. Bias vs Variance Tradeoff
2. Underfitting vs Overfitting
3. K-Fold Cross-Validation
4. Hyperparameter Tuning with GridSearchCV
5. RandomizedSearchCV for Large Parameter Spaces
6. The ML Pipeline: Automating the Workflow

The tuning loop

  flowchart LR
  D[Data] --> P[Preprocess]
  P --> M[Train model]
  M --> E[Evaluate]
  E --> T[Tune]
  T --> M