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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.
IBM has been pushing laborious on being a aggressive menace in enterprise cloud, however is much behind the leaders like Amazon AWS, Microsoft Azure and Google Cloud. It’s newest technique to turn out to be extra related, along with shopping for RedHat for its cloud experience, is to develop a sequence of “straightforward on-ramp” Cloud Paks that it claims can considerably scale back the period of time needed for enterprises to be cloud-enabled. However is that this sufficient to alter the potential of IBM to compete in a extremely aggressive fashionable cloud surroundings?
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.
