Exploring the ML Tooling Landscape (Part 3 of 3)


The previous blog post in this series considered the current state of the ML tooling ecosystem and how this was reflected in ML adoption in industry. The main takeaway was the widespread use of propriety tooling amongst companies in this field, with a correspondingly diverse and splintered ML tooling market. The post ended by looking at some emerging near-term trends, highlighting the predominance of data observability and related tools, as well as the emergence of MLOps startups. This blog post will pick up from this previous thread to discuss some of the key trends in ML tooling that are likely to dominate in the near future -- or at least ones I want to talk about! As indicated in the previous blog post, I want to focus on MLOps, AutoML, and data-centric AI.

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