EPISODE · Mar 10, 2021 · 32 MIN
Concurrent is not parallel - Part 1 (Ep. 142)
from Data Science at Home · host Francesco Gadaleta <frag>
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 SponsorsThis 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. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit datascienceathome.substack.com
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Concurrent is not parallel - Part 1 (Ep. 142)
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