Parallel Computing and Scientific Machine Learning
In Fall 2020 and Spring 2021, this was MIT's 18.337J/6.338J: Parallel Computing and Scientific Machine Learning course. Now these lectures and notes serve as a standalone book resource. https://github.com/SciML/SciMLBook Chris Rackauckas, Massachusetts Institute of Technology Additional information on these topics can be found at: https://sciml.ai/ and other Julia programming language sites Many of these descriptions originated on https://www.stochasticlifestyle.com/
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Parallel Computing and Scientific Machine Learning (@scimlorg) is a data science YouTube channel with 5.6K subscribers. With 25 videos and 228.6K total views, the channel averages 5K views per video. Parallel Computing and Scientific Machine Learning has an engagement rate of 1.78%, placing it in the top 62% of data science educators on the platform. The channel uploads on a weekly basis, making it a inactive creator in the developer education space. Parallel Computing and Scientific Machine Learning covers technologies including Git & GitHub.
