Sveriges mest populära poddar
Data Skeptic
VetenskapTeknologi

Visualization and Interpretability

36 min•31 januari 2020

Enrico Bertini joins us to discuss how data visualization can be used to help make machine learning more interpretable and explainable.

Find out more about Enrico at http://enrico.bertini.io/.

More from Enrico with co-host Moritz Stefaner on the Data Stories podcast!

Fler avsnitt av Data Skeptic

Visa alla avsnitt av Data Skeptic
Book Ratings and Recommendations
•39 min
Disentanglement and Interpretability in Recommender Systems
•31 min
Collective Altruism in Recommender Systems
•55 min
Niche vs Mainstream
•34 min
Healthy Friction in Job Recommender Systems
•27 min
Fairness in PCA-Based Recommenders
•50 min
Video Recommendations in Industry
•38 min
Eye Tracking in Recommender Systems
•52 min
Cracking the Cold Start Problem
•40 min
Designing Recommender Systems for Digital Humanities
•37 min

Data Skeptic med Kyle Polich finns tillgänglig på flera plattformar. Informationen på denna sida kommer från offentliga podd-flöden.