Published May 19, 2022
Data Debt in Machine Learning with D. Sculley - #574
D. Sculley from Google Brain delves into the critical roles of data quality, evaluation techniques, and causal inference in machine learning, emphasizing the impact of data debt on AI systems. This episode uncovers strategies for enhancing model reliability through robust data curation and the innovative use of causal inference graphs in stress testing AI models.
Topics covered
Popular Clips
Episode Highlights
Related Episodes
AI and the Responsible Data Economy with Dawn Song - #403
Answers 383 questions
Real-Time ML Workflows at Capital One with Disha Singla - 606
Answers 383 questions
Cognitive Biases in Data Science with Drew Conway - #39
Answers 383 questions
Systems and Software for Machine Learning at Scale with Jeff Dean - #124
Answers 383 questions
Machine Learning: A New Approach to Drug Discovery with Daphne Koller - #332
Answers 383 questions
Advancing Machine Learning at Capital One with Dave Castillo - #328
Answers 383 questions
Data Governance for Data Science with Adam Wood - #578
Answers 383 questions
Scaling Enterprise ML in 2020: Still Hard! with Sushil Thomas - #429
Answers 383 questions
Trends in Machine Learning & Deep Learning with Zack Lipton - #334
Answers 383 questions
Offensive vs Defensive Data Science with Deep Varma - #25
Answers 383 questionsResponsible Data Science in the Fight Against COVID-19 (Coronavirus)
Answers 383 questions
Data Innovation & AI at Capital One with Adam Wenchel - #147
Answers 383 questions
Machine Learning Commerce at Square with Marsal Gavalda - #384
Answers 383 questions
Trends in Machine Learning & Deep Learning with Zachary Lipton - #556
Answers 383 questions
