Model Evaluation

Deep Dive Into Error Analysis and Model Debugging in Machine Learning (and Deep Learning)

“Winning a Kaggle competition does not prepare you for real-world data science!” I’ve heard that a lot. When I was still a newbie, I wondered “What? I got 99% accuracy on the leaderboard. That’s a...

by Dhruvil Karani

The Ultimate Guide to Evaluation and Selection of Models in Machine Learning

by Samadrita Gosh, November 2nd, 2020

Brier Score: Understanding Model Calibration

by anasselhoud, October 21st, 2020

PyTorch Loss Functions: The Ultimate Guide

by alfrickopidi, October 16th, 2020

Cross-Validation in Machine Learning: How to Do It Right

by Vladimir Lyashenko, October 6th, 2020

Binary Classification: Tips and Tricks from 10 Kaggle Competitions

by Derrick Mwiti, August 12th, 2020

Explainable and Reproducible Machine Learning Model Development with DALEX and Neptune

by Jakub Czakon, August 5th, 2020

Keras Loss Functions: Everything You Need To Know

by Derrick Mwiti, July 8th, 2020

Best Practices for Dealing with Concept Drift

by Shhibsankar Das, June 29th, 2020

How to Track Machine Learning Model Metrics in Your Projects

by Jakub Czakon, June 22nd, 2020

Tabular Data Binary Classification: All Tips and Tricks from 5 Kaggle Competitions

by Shahul ES, June 15th, 2020

The Best Tools to Visualize Metrics and Hyperparameters of Machine Learning Experiments

by Pawel Kijko, May 21st, 2020

Keras Metrics: Everything You Need To Know

by Derrick Mwiti, January 27th, 2020