Speeding up Python code has traditionally been achieved by writing C/C++ — an alien world for most Python users. Today, you can write high performance code in Julia instead, which is much much easier for Python users. This tutorial will give you hands-on experience writing a Python library that incorporates Julia for performance optimization.
Stephan Sahm is founder of the Julia consultancy Jolin.io, full stack senior data/ml consultant, and organizer of the Julia User Group Munich.
Stephan Sahm's top interest are in green computing, probabilistic programming, real time analysis, big data, applied machine learning and in general industry applications of Julia.
Aside Julia and sustainable computing, he likes chatting about Philosophy of Mind, Ethics, Consciousness, Artificial Intelligence and other Cognitive Science topics.