Check out LLMon 🍋 - our new LLM Monitoring solution

All Knowledge

The Giskard hub

HomeBlogNewsTutorials
SHAP values - based on https://github.com/shap/shap

Opening the Black Box: Using SHAP values to explain and enhance Machine Learning models

Mykyta Alekseiev - ML Engineering Intern
Mykyta Alekseiev
Testing Classification Models for Fraud Detection with Giskard

Testing Machine Learning Classification models for fraud detection

Happiness Omale - Technical writer
Happiness Omale
Robot reading a newspaper generated by open-source generative AI model ControlNet and Stable Diffusion

How to evaluate and load a PyTorch model with Giskard?

Favour Kelvin
Favour Kelvin
Picture illustrating gender bias generated by DALL-E2

How to test the fairness of ML models? The 80% rule to measure the disparate impact

Rabah Abdul Khalek
Rabah Abdul Khalek
Happy green robot generated by open-source generative AI model Stable Diffusion

How to deploy a robust HuggingFace model for sentiment analysis into production?

Princy Pappachan
Princy Pappachan
Metamorphic testing

How to test ML models? #4 🎚 Metamorphic testing

Jean-Marie John-Mathews
Jean-Marie John-Mathews, Ph.D.
Numerical data drift

How to test ML models? #3 📈 Numerical data drift

Jean-Marie John-Mathews
Jean-Marie John-Mathews, Ph.D.
Cars drifting

How to test ML models #2 🧱 Categorical data drift

Jean-Marie John-Mathews
Jean-Marie John-Mathews, Ph.D.
Zoom in on the problem

How to test ML models? #1 👉 Introduction

Jean-Marie John-Mathews
Jean-Marie John-Mathews, Ph.D.