Free Virtual Conference Will Feature Speakers From 30 Organizations Including DoorDash, Etsy, Google, Lemonade, LinkedIn, Microsoft, Netflix, Pinterest, Spotify and Stitch Fix
Tecton, the enterprise feature store company, announced the line-up for apply(), a virtual conference that it is hosting on data engineering for applied machine learning (ML) April 21 – 22.
apply() is a practitioner-focused community event for data and ML teams to discuss the practical data engineering challenges faced when building ML for the real world. Participants will share best practice development patterns, tools of choice and emerging architectures they use to successfully build and manage production ML applications. Everything is on the table from managing labeling pipelines to transforming features in real-time to serving at scale.
apply() will feature speakers from Algorithmia, Anyscale, Atlassian, Confluent, Cookpad, Deloitte, DoorDash, Etsy, Fiddler, Google, Intuit, Lemonade, LinkedIn, McKinsey, Mercado Libre, Microsoft, MLOps.Community, Monte Carlo, Netflix, Noteable, Pinterest, Provectus, Redis Labs, Snorkel AI, Spotify, Stanford, StitchFix, Tecton, Tide and Ursa.
“We’re excited to be hosting the apply() conference,” said Mike Del Balso, co-founder and CEO of Tecton. “This will be the first community event focused exclusively on data engineering challenges of applied ML. It’s a great opportunity for practitioners to learn from experts and collaborate with peers.”
Del Balso is doing a session at apply() with Willem Pienaar, creator and an official committer of Feast and architect at Tecton, on “Rethinking Feature Stores.” Feature stores have emerged as a pivotal component in the modern machine learning stack. They solve some of the toughest challenges in data for machine learning, namely feature computation, storage, validation, serving and reuse.
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