Rajiv Shah

Rajiv Shah, a data scientist at DataRobot and professor at the University of Illinois at Chicago, dives into the critical issue of data leakage in machine learning. He explains how this hidden menace can skew model results, emphasizing techniques like activation maps to spot leakage. The conversation also covers the ethical implications of data handling and the importance of robust model development practices. Rajiv encourages aspiring data scientists to prioritize foundational skills over trends for successful machine learning.