Build resilient machine learning models; advice for ML careers - Gerald Friedland The Data Scientist Show #001

Gerald Friedland is the CTO of an AI company (Brainome) and a professor at UC Berkeley. Listen to his advice on how to build more resilient machine learning models and get inspired by his career journey!  If you like the show subscribe to the channel and give us a 5-star review. Subscribe to Daliana's newsletter on www.dalianaliu.com/ for more on data science and career. Gerald’s LinkedIn: https://www.linkedin.com/in/geraldfriedland/ Gerald’s Class: https://www2.eecs.berkeley.edu/Courses/CS294_3438/ Gerald’s Youtube Lectures: https://www.youtube.com/playlist?list=PL17CtGMLr0XzOsLydB0jik4UpEyoW5SOx Daliana's LinkedIn: https://www.linkedin.com/in/dalianaliu/ Daliana's Twitter: https://twitter.com/DalianaLiu (00:00:00) Introduction (00:01:06) How did he get into machine learning (00:12:13) How to Reduce Overfitting (00:22:15) Technology in Brainome (00:24:13) Brainome vs auto ML (00:27:08) Measurement of a data-centric approach (00:27:32) Data Drift (00:32:28) Courses to take (00:34:33) Information theory (00:38:06) Advice for students in grad school (00:42:43) Dealing with failure and stress (00:44:05) The underdog story (00:49:12) Who is Gerald Friedland (00:50:00) Inspiration of Gerald (00:51:08) Future of machine learning (00:52:36) Tips for asking the right questions (00:53:40) Question your assumptions (00:54:10) Favorite books and courses (00:56:34) Advice on machine learning (00:57:52) Ideal qualities of an ML engineer