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Why Model Explainability is The Next Data Science Superpower

Towards Data Science

I’ve interviewed many data scientists in the last 10 years, and model explainability techniques are my favorite topic to distinguish the very best data scientists from the average. Some people think…

If Your Model Isn’t Explainable, Is It Really Your Model?

Towards Data Science

Explainability in machine learning and AI systems is no longer a nice-to-have feature, but an essential component for any product that users and policymakers can consider safe, reliable, and fair…

Are All Explainable Models Trustworthy?

Towards Data Science

Explainable AI or Explainable Data Science is one of the top buzzwords of Data Science at the moment. Models that are explainable are seen as the answer to many of recently recognised problems with…

Mixing Art into the Science of Model Explainability

Towards Data Science

Overview on Explainable Boosting Machine and an approach for converting ML explanation to more human-friendly explanation. Fig.1 — A lego figure on my desk, Image by the author. 1\. Science of ML exp...

An overview of model explainability in modern machine learning

Towards Data Science

How we can understand black box machine learning models, and why it matters

Machine Learning Explainability

Towards Data Science

Recently, I did the micro course Machine Learning Explainability on kaggle.com. I can highly recommend this course as I have learned a lot of useful methods to analyse a trained ML model. For a brief…...

Which models are interpretable?

Towards Data Science

A brief overview of some interpretable machine learning models Continue reading on Towards Data Science

Machine Learning Models Explainability — definitions, importance, techniques, and tools

Towards AI

Machine Learning Models Explainability — Definitions, Importance, Techniques, And Tools Techniques (LIME, SHAP, PDP, ICE, DeepLIFT, others), libraries, and other details of Model Explainability Photo...

Model Explainability, Revisited: SHAP and Beyond

Towards Data Science

The rapid rise of large language models has dominated much of the conversation around AI in recent months—which is understandable, given LLMs’ novelty and the speed of their integration into the daily...

Mastering Model Explainability in Python

Towards Data Science

For data scientists, a key part of interpreting machine learning models is understanding which factors impact predictions. In order to effectively use machine learning in their decision-making…

How to Ensure You Can Explain Why Your Model Makes Predictions

Towards Data Science

Techniques to extract information from your model to explain why it makes predictions Continue reading on Towards Data Science

Model Explainability and JRT AI

Towards Data Science

Model explainability is getting more and more common and mainstream into AI models and usage in today’s scenario. Expectation is to understand what is happening in detail and the “how” part of any…