Prasad Chalasani is the SVP of Data Science at Media Math, leading the development of innovative, proprietary scalable algorithms and analytics that leverage massive amounts of data to power smarter digital marketing for the world’s leading advertisers. Prior to joining Media Math, Prasad led Data Science at Yahoo Research, and before that worked for 10 years as a quantitative researcher and portfolio manager of statistical trading strategies at hedge funds and at Goldman Sachs. Prasad holds a PhD in Machine Learning from CMU and BTech in Computer Science from IIT.
In Part 2 of our series, the ML novice realized that generalization is a key ingredient of a true ML algorithm. In today’s post we continue the conversation (the novice is in bold italics) to elabo... Read more
In the first post of our non-technical ML intro series we discussed some general characteristics of ML tasks. In this post we take a first baby step towards understanding how learning algorithms wo... Read more
With the increasingly vast volumes of data generated by enterprises, relying on static rule-based decision systems is no longer competitive; instead, there is an unprecedented opportunity to optimi... Read more