mccormick.northwestern.edu

Exploring the Connections Among Machine Learning, Interpretability, and Logic

The field of interpretability investigates what machine learning (ML) models are learning from training datasets, the causes and effects of changes within a model, and the justifications behind its ...
insideHPC

Machine Learning Interpretability with Driverless AI

Data visualization techniques for representing high-degree interactions and nuanced data structures. Contemporary linear model variants that incorporate machine learning and are appropriate for use in ...
ascopubs.org

Improved Interpretability of Machine Learning Model Using Unsupervised Clustering: Predicting Time to First Treatment in Chronic Lymphocytic Leukemia

PROSPeCT: A Predictive Research Online System for Prostate Cancer Tasks Time to event is an important aspect of clinical decision making. This is particularly true when diseases have highly ...
KXAN

Bhusan Chettri's Launched Tutorials Series of AI, Machine Learning, Deep Learning and Their Interpretability

Dr Bhusan Chettri who earned his PhD from Queen Mary University of London aims at providing an overview of Machine Learning and AI interpretability. LONDON, UNITED ...
The Globe and Mail

Dan Herbatschek Leads New Initiative in New York and Los Angeles to Advance Transparency and Interpretability in Machine Learning

The applied mathematician and Ramsey Theory Group founder launches a mission to reshape how organizations understand and trust AI. Los Angeles, CA - Dec 2, 2025 -Dan Herbatschek, Founder and CEO of ...

What is the Difference Between Deep Learning and Machine Learning

We have explained the difference between Deep Learning and Machine Learning in simple language with practical use cases.