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.
Rearchitecting for the cloud ought to embrace containerization of main software elements in one thing like Docker, which may then be managed by an open sourced Kubernetes orchestration framework for optimization of assets and effectivity. We anticipate that containerization will finally be the defacto normal for working workloads within the cloud, and never simply the wrapped up monolithic app implementations introduced over from consumer server implementations.
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.
