The Banana Data Podcast
Data Nuance & Human-in-the-Loop Monitoring
Chapters
The Banana Data Podcast
Data Nuance & Human-in-the-Loop Monitoring
Jun 05, 2020 Season 3 Episode 6
Dataiku

For our Season 3 finale, we're taking a look at model accuracy, the threat of generalized results, and how to understand and demonstrate the nuanced results of your models. Is the onus on scientists and journalists to subdue buzzy headlines or should media consumers be more wary of extrapolated statistics? 

We also take a peek into how the NYT applies Machine Learning to their comment moderation, and how human-in-the-loop monitoring works behind the scenes, especially in fast-paced and ethically questioning environments.

This is also our final episode with Will on the team - and we'd like to thank him for all of the hard work, great ideas, and many laughs he's provided with us along the way. He's been an invaluable team member, but do not fear! Season 4 will bring many new and fresh surprises to the Banana Data Team. Stay tuned.....

 Banana Riddle Answer: 49

 All models are wrong, but some are completely wrong (Royal Statistical Society)

 To Apply Machine Learning Responsibly, We Use It in Moderation by By Matthew J. Salganik and Robin C. Lee (NYT Open)