Announcing apply()'s Speaker Lineup | Tecton

Tecton

Announcing apply()’s Speaker Lineup

By March 31, 2021

Tecton is hosting apply(): the ML Data Engineering conference on April 21 and 22, bringing together industry thought leaders and practitioners from over 30 organizations to share and discuss the current and future state of ML data engineering. This conference will be entirely virtual, making it easier for us to bring together speakers and participants from across the country and the globe to join the discussion.

At Tecton, we believe the advent of operational ML (ML used for online, automated decision making) is redefining software today by delivering magical customer experiences and re-inventing business processes. In our experience, the complexity of ML data engineering is the biggest barrier between most data teams and transforming their applications and user experiences with operational ML. We organized apply() to get the best and brightest minds in ML data engineering into one (Zoom) room to share their findings and best practices with the broader community.

The apply() conference is bringing together speakers from across industries and backgrounds to cover topics that are top of mind for ML data scientists and engineers today including: online serving, data observability, feature stores, model performance management, MLOps best-practices, scaling ML at large organizations, and more. Our speakers include innovators and leaders like Wes McKinney (Ursa, Pandas, Apache Arrow), Chip Huyen (Stanford), Niall Murphy (Microsoft Azure), Todd Underwood (Google), and more from companies like Confluent, DoorDash, Etsy, Netflix, Pinterest, Redis Labs, Spotify, and Stitch Fix. Speakers will give either in-depth 30-minute session talks including Q&A or concise 10-minute lightning talks, sharing their experiences and perspectives on ML data engineering.

To learn more about apply() and reserve your seat today, simply visit the event website. To view our lineup of speakers, check out our agenda of events, and make sure to join the apply() Slack channel to participate in the conversation.


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