Python* has become an instrumental tool for those looking for a high productivity language for a variety of programming tasks including advanced numerical work. Learn how Intel brings high performance, easy accessibility, and integrated workflow to Python* in numerical, scientific, and the machine learning space.
We will compare and contrast Intel-optimized NumPy, SciPy, and scikit-learn, and learn about pyDAAL (Python APIs to Intel® Data Analytics Acceleration Library) with examples. For those needing more compute power at the ready, we will also be talking about the Remote Access Program, which gives access to fully built Intel® Xeon Phi™ clusters to test one’s code on.
Users can expect to learn the following:
David Liu is a Technical Consultant Engineer at Intel Corporation in Austin, Texas, where he represents Intel’s Python products and projects. He is focused on solving customer problems in Python while simultaneously developing and shaping Intel’s software products to match customer needs. In the past, he worked as a software engineer utilizing Python in machine learning, network infrastructure, and web work. David holds an MS in Software Engineering from the University of Texas at Austin.