Why Software Engineering Processes and Tools Don't Work for Machine Learning

Written by comet.ml | Published 2019/12/05
Tech Story Tags: machine-learning | machine-learning-use-cases | machine-learning-tools | comet.ml | model-accuracy | software-development | good-company | latest-tech-stories

TLDR Data Scientist Niko Laskaris explains why data scientists and teams can’t rely on the tools and processes that software engineering teams have been using for the last 20 years for machine learning (ML) He argues that the provable correctness of software engineering does not extend to AI and machine learning. The adoption of tools designed specifically for AI will help practitioners unlock and enable the type of revolutionary transformation Ng is speaking about. Laskari: “AI is the next big transformation,” and we’re watching the transformation unfold.via the TL;DR App

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Written by comet.ml | Allowing data scientists and teams the ability to track, compare, explain, reproduce ML experiments.
Published by HackerNoon on 2019/12/05