Lecture 9 Model Evaluation in Machine Learning

In-class Material

1. Slides

2. Notebook

Extra Reading

1. Slice finder

2. Why model calibration matters and how to achieve it

3. Calibrated recommendations

4. Data Versioning and Reproducible ML with DVC and MLflow

5. A simple way to calibrate your neural network.

6. How to automate model tuning with HyperOpt

7. Advanced Sklearn Pipelines

8. MLflow Tutorial