A Crash Course on Model Interpretability – Part 2
A deep dive into interpretability methods, why they matter, along with their intuition, considerations, how to avoid being misled, and code.
A Crash Course on Model Interpretability – Part 1
A deep dive into PDPs and ICE plots, along with their intuition, considerations, how to avoid being misled, and code.
15 Ways to Optimize Neural Network Training (With Implementation)
Techniques that help you become a "machine learning engineer" from a "machine learning model developer."
A Mathematical Deep Dive Into the Curse of Dimensionality
Mathematically understanding the surprising phenomena that arise when dealing with data in high dimensions.
