20+ Interpretability Online Courses for 2024 | Explore Free Courses & Certifications

Explaining Model Decisions and Fixing Them Through Human Feedback

Optimizing for Interpretability in Deep Neural Networks - Mike Wu

Machine Learning Modeling Pipelines in Production

Yannic Kilcher

Neural Networks Are Decision Trees - With Alexander Mattick

Alan Turing Institute

Transparency in Algorithmic Decision-Making - Karen Yeung, Birmingham Law School

Alan Turing Institute

Beyond Tech - Machine Learning in Science & Policy - Professor David Dunson, Duke

Alan Turing Institute

Be Prepared to Show Your Working! - Professor Sir David Spiegelhalter

Alan Turing Institute

Introduction to Data Ethics - Brent Mittelstadt

Alan Turing Institute

Machine Learning and Data Science for Medicine - A Vision, Some Progress and Opportunities

Graham Neubig

CMU Neural Nets for NLP: Model Interpretation

Open Data Science

Responsible AI Dashboard - A Tool for Operationalizing Responsible AI

MITCBMM

Adversarial Examples and Human-ML Alignment

Association for Computing Machinery (ACM)

Interpretable Active Learning

Simons Institute

Interpreting Deep Neural Networks

GOTO Conferences

One Does Not Simply Put Machine Learning into Production

Most common

Popular subjects

Popular courses

Interpretability Courses and Certifications

Explaining Model Decisions and Fixing Them Through Human Feedback

Optimizing for Interpretability in Deep Neural Networks - Mike Wu

Machine Learning Modeling Pipelines in Production

Neural Networks Are Decision Trees - With Alexander Mattick

Transparency in Algorithmic Decision-Making - Karen Yeung, Birmingham Law School

Beyond Tech - Machine Learning in Science & Policy - Professor David Dunson, Duke

Be Prepared to Show Your Working! - Professor Sir David Spiegelhalter

Introduction to Data Ethics - Brent Mittelstadt

Machine Learning and Data Science for Medicine - A Vision, Some Progress and Opportunities

CMU Neural Nets for NLP: Model Interpretation

Responsible AI Dashboard - A Tool for Operationalizing Responsible AI

Adversarial Examples and Human-ML Alignment

Interpretable Active Learning

Interpreting Deep Neural Networks

One Does Not Simply Put Machine Learning into Production

Interpretability Courses and Certifications

Explaining Model Decisions and Fixing Them Through Human Feedback

Optimizing for Interpretability in Deep Neural Networks - Mike Wu

Machine Learning Modeling Pipelines in Production

Neural Networks Are Decision Trees - With Alexander Mattick

Transparency in Algorithmic Decision-Making - Karen Yeung, Birmingham Law School

Beyond Tech - Machine Learning in Science & Policy - Professor David Dunson, Duke

Be Prepared to Show Your Working! - Professor Sir David Spiegelhalter

Introduction to Data Ethics - Brent Mittelstadt

Machine Learning and Data Science for Medicine - A Vision, Some Progress and Opportunities

CMU Neural Nets for NLP: Model Interpretation

Responsible AI Dashboard - A Tool for Operationalizing Responsible AI

Adversarial Examples and Human-ML Alignment

Interpretable Active Learning

Interpreting Deep Neural Networks

One Does Not Simply Put Machine Learning into Production