Concurrent is not parallel - Part 2 (Ep. 143)

In plain English, concurrent and parallel are synonyms. Not for a CPU. And definitely not for programmers. In this episode I summarize the ways to parallelize on different architectures and operating systems. Rock-star data scientists must know how concurrency works and when to use it IMHO.   Our Sponsors This episode is supported by Chapman’s Schmid College of Science and Technology, where master’s and PhD students join in cutting-edge research as they prepare to take the next big leap in their professional journey.To learn more about the innovative tools and collaborative approach that distinguish the Chapman program in Computational and Data Sciences, visit chapman.edu/datascience   Amethix use advanced Artificial Intelligence and Machine Learning to build data platforms and predictive engines in domain like finance, healthcare, pharmaceuticals, logistics, energy. Amethix provide solutions to collect and secure data with higher transparency and disintermediation, and build the statistical models that will support your business.     Useful Links http://web.mit.edu/6.005/www/fa14/classes/17-concurrency/ https://doc.rust-lang.org/book/ch16-00-concurrency.html https://urban-institute.medium.com/using-multiprocessing-to-make-python-code-faster-23ea5ef996ba