Archives
- Thu 14 April 2022
- How to become a data scientist, part 3: tell people about your work
- Thu 07 October 2021
- What if Recommendation Algorithms Like Facebook’s Grappled Directly with Bad Content?
- Tue 13 August 2019
- Should you explain your predictions with SHAP or IG?
- Wed 31 July 2019
- Causality in model explanations and in the real world
- Mon 22 July 2019
- “Hey, what’s that?” Debugging predictions using explanations
- Mon 03 June 2019
- A gentle introduction to GA2Ms, a white box model
- Wed 08 May 2019
- Humans choose, AI does not
- Tue 23 April 2019
- A gentle introduction to algorithmic fairness
- Thu 21 March 2019
- Case study: explaining credit modeling predictions with SHAP
- Mon 11 February 2019
- Mary and John: using first name to predict sex in the US works quite well
- Thu 15 June 2017
- How to become a data scientist, part 2: try to solve the problem
- Thu 27 April 2017
- How to become a data scientist, part 1: find a good problem
- Fri 21 April 2017
- How to become a data scientist, part 0: introduction