from AI/ML Technical Lead
AI/ML technical lead in Qlue and high performance computing enthusiast, using Python in production environment for Qlue smart city solutions development.
"The basic concepts & applications of concurrency & parallelism, how to choose them for your projects, their built-in packages, and sample cases, all in Python."
I'm an AI enthusiast backed by STEM education and interdisciplinary experiences whose encouraging the research and development of artificial intelligence and machine learning to solve various computer vision task problems. I love to plan and build efficient, effective, and high performance solutions to solve various industrial, business, even personal needs throughout utilization of multiple technologies.
_Dealing with concurrency becomes hard when we lack the ‘working knowledge’ and best practices are not followed._ ‒ Ramith Jayasinghe, Experienced Software Engineer.
This talk will give you a brief description about the generic terms of concurrency and parallelism, multitasking styles, and task bounds to make y'all first understand the basic concepts of concurrency and parallelism. The story of Python interpreter implementation for embracing concurrency will be given, so that y'all know how your _friend_ is working. Popular Python built-in packages for concurrent programming (i.e. multithreading, multiprocessing, and asyncio) will be shown, given some minimum working example. At last, by this talk you could choose what is the best concurrent programming approach for your project and extend yourself into more wild 3rd party packages for the sake of concurrency.