This Aurora Learning Paths series will go into detail about how to apply key Intel architectural innovations and libraries via smart application of NumPy, SciPy, and Pandas techniques to achieve amazing performance gains.
We’ll delve into NumPy sorting, aggregations, universal functions, broadcasting and fancy slicing, sorting, and other techniques powered by oneAPI. Learn how to achieve performance gains by replacing Python loop-centric or list comprehension applications with smarter equivalents that are more maintainable, more efficient, and much faster on current and future innovations in Intel hardware and oneAPI software libraries!
Bob Chesebrough is a Technical Evangelist in the Intel Developer Academy. His educational background is in physics. His industry experience has been in software development and application/performance engineering for Fortune 100 companies and national laboratories for over three decades. He is a data scientist, using machine learning/deep learning for eight years while working for Intel and other high-tech companies. His other passion is hunting for dinosaur bones in the deserts of the Southwestern U.S. with his family (and creating AI likelihood maps to help).
This event is free, but registration is required.