The hosts of Becoming a Data Scientist podcast, Partially Derivative podcast, Adversarial Learning podcast, and some other awesome data people that do elections forecasting for their day jobs joined together for this talk about the US election and the subsequent major questions surrounding the predictions, since basically all of them heavily leaned toward a different overall outcome than we got. If you’re interested at all in data science surrounding political campaigns, this episode is a must-listen!
Episode Audio (mp3) – also available on iTunes, Stitcher, etc.
(note, there is no video for this episode)
On the panel:
- Chris Albon (Twitter) (Website)
- Joel Grus (Twitter) (Website)
- Natalie Jackson (Twitter) (Website)
- Jonathon Morgan (Twitter) (Website)
- Andrew Musselman (Twitter)
- Mark Stephenson (Twitter) (Website)
- Renee Teate (Twitter) (Website)
- Andrew Therriault (Twitter) (Website)
Source: becomingadatascientist.com – Becoming a Data Scientist Podcast Special Episode