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The video beneath, “Pondering Sparse and Dense,” is the presentation by Paco Nathan from dwell@Manning Developer Productiveness Convention, June 15, 2021. In a Put up-Moore’s Regulation world, how do information science and information engineering want to vary? This discuss presents design patterns for idiomatic programming in Python in order that {hardware} can optimize machine studying workflows.
Whereas a lot hype has been produced concerning the speedy tempo of enterprise cloud deployments, in actuality we estimate lower than 25 % of enterprise workloads are at the moment being run within the cloud. That doesn’t negate the significance of the expansion of cloud computing – however it does set some parameters round simply how prevalent it at the moment is, and the way troublesome it's to maneuver enterprise workloads to a cloud structure.
You’ll hear about methods of dealing with information which are both “sparse” or “dense” relying on the stage of ML workflow – plus, easy methods to leverage profiling instruments in Python to know easy methods to benefit from the {hardware}. The discuss additionally considers 4 key abstractions that are outdoors of most programming languages, however very important in information science work.
