Standard 3 stops to get here

Baseline Model

A simple reference model (random, majority class, simple heuristic) used to benchmark more complex models against.

Your route here

3 stops · basics first
  1. Dataset ✓ understood

    A collection of data examples used for training, validating, or testing machine learning models.

  2. Train-Test Split ✓ understood

    Dividing a dataset into separate portions for training the model and evaluating its performance on unseen data.

  3. Test Set ✓ understood

    A final portion of data unseen during training and validation, used for unbiased evaluation of model performance.

  4. Baseline Model · you are here ✓ understood

Where it sits

Before this

Test Set
Baseline Model

Leads to

Nothing yet: a destination in its own right.

Explore nearby

Evaluation Benchmark A standardized dataset and task used to compare model performance across different approaches (ImageNet, GLUE, SuperGLUE). Evaluation A/B Testing Comparing two model versions in production by routing traffic to each and measuring performance differences. Evaluation Accuracy The proportion of correct predictions out of total predictions, a basic classification metric. Shipping AI Experiment Tracking Recording hyperparameters, metrics, and artifacts from training runs for comparison and reproducibility.