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 ...
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 ...
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 ...
Diginomica

AI explainability and interpretability - we have a long way to go

AI explainability remains an important preoccupation - enough so to earn the shiny acronym of XAI. There are notable developments in AI explainability and interpretability to assess. How much progress ...
Quanta Magazine

A New Approach to Understanding How Machines Think

Neural networks are famously incomprehensible — a computer can come up with a good answer, but not be able to explain what led to the conclusion. Been Kim is developing a “translator for humans” so ...
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 ...

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.