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October 12, 2022 by Gaetan Castelein
Real-time ML is when an app uses an ML model to autonomously and continuously make decisions that impact the decision in real time. Read to learn about the journey to real-time ML.
Operational & Real-Time Machine Learning
October 6, 2022 by Pauline Brown
Tecton 0.5 has exciting new capabilities designed to give Tecton users more flexibility and control of their features and underlying systems. Read this post to learn more about these capabilties.
Product Updates
September 14, 2022 by Mike Del Balso
In this post, we take a look at the early days of getting ML into production, where we are today, and some predictions of what it will be like to build ML applications in the future.
Thought Leadership
August 23, 2022 by Alex Guziel, Yoni Michael
Learn how Tecton’s canary process was designed to keep Tecton’s feature platform reliable, stable, and scalable.
Engineering
August 16, 2022 by David Hershey
The hardest part of real-time machine learning is building real-time data pipelines. Learn how you can avoid common challenges in this post.
Operational & Real-Time Machine LearningThought Leadership
August 4, 2022 by David Hershey
Getting ML systems into production has always been (and still is) challenging. Learn how to use Tecton and Databricks to overcome those challenges and build an MVP for a real-time ML system in 15 minutes.
Partners & IntegrationsTutorials
July 28, 2022 by Mike Del Balso
Learn how achieving the flywheel effect with ML can help you and your team quickly iterate on models, creating a compounding effect that results in high performance and reliability.
Thought LeadershipOperational & Real-Time Machine Learning
July 12, 2022 by Mike Del Balso
Tecton has raised $100M in a Series C funding round to help make real-time ML accessible to everyone.
Announcements
June 22, 2022 by Pauline Brown
Tecton is now available to all Databricks customers on AWS. The integration enables teams to build production-ready feature pipelines and serve them at scale with only a few lines of code.
Partners & Integrations
May 26, 2022 by Kevin Stumpf
In this post, Kevin Stumpf, CTO of Tecton, describes what operational ML really is and gives practical examples to understand how it works.
May 16, 2022 by David Hershey
How should you organize an ML team? Do centralized data teams work? In this article, David Hershey, solutions architect at Tecton, describes a common pattern we've seen across hundreds of companies using machine learning: centralized data teams …
May 11, 2022 by Mike Del Balso
During apply(meetup), Ben Wilson, from Databricks, gave a lightning talk on how ML projects shouldn't be built in isolation. At Tecton, we believe that great ML infra should integrate deeply with existing data infrastructure while providing …
Thought LeadershipFeature Stores
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