613: Causal Machine Learning
Super Data Science: ML & AI Podcast with Jon Krohn
00:00
Applying Causal Methods in Machine Learning and Hiring Practices at Microsoft Research
The chapter explores the utilization of causal methods for invariance discovery in deep learning models, focusing on identifying consistent patterns with causal graphs. The discussion extends to the benefits and limitations of using the Copilot programming tool for code generation based on natural language inputs. Additionally, the chapter delves into the hiring process at Microsoft Research, emphasizing the criteria for researcher roles and the significance of impactful research in collaboration with academia.
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