This section contains examples for how to use Tecton. The examples intend to cover most common Tecton workflows, and will grow as new functionality is added. The examples focus on user actions and have reference code that can be copy, pasted, and modified to your specific needs. If you are looking for a specific reference that is not yet available,

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Pass the Feature Service name and the join keys as parameters. The response is a JSON object. Last year, three former Uber engineers left the company to form a startup called Tecton.ai. They envisioned an operational machine learning platform for companies struggling to integrate the technology into their products. On Tuesday, the startup announced that it has raised $20 million in Series A funding.

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Three former Uber engineers, who helped build the company’s Michelangelo machine learning platform, left the company last year to form Tecton.ai and build an operational machine learning platform Tecton is a platform that morphs raw data into AI models that can be successfully deployed. And yes, this is far from a trivial process. Tecton is an Enterprise Feature Store. It empowers data scientists and engineers to productionize, share, monitor, and serve features. Tecton has sent you a link with a Databricks workspace to use - in your "Welcome to Tecton" email. The "Shared" workspace should have a "Tecton in 10 Minutes" notebook to walk through.

In a company blog post, Del Balso noted that Tecton isn’t ready for a public release just yet. 2020-04-30 · Tecton.ai emerged from stealth and formally launched with its data platform for machine learning.

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29 likes · 1 talking about this. Feature Store for Machine Learning, from the creators of Uber Michelangelo. Build a library of great features. Serve them in Tecton’s total funding is now at $60 million, with the recent funding aimed at accelerating product innovation and go-to-market activities.

Machine learning is an artificial intelligence (AI) application that allows systems to learn Uber Michelangelo creators founded Tecton.ai to provide world-class

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Founders. Mike Del Balso; Jeremy Hermann; Kevin Stumpf Website. www.tecton.ai. Ownership Status. Privately Held (backing). Financing Status.
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ML in production “Based on our experience building Uber Michelangelo, we know that feature stores are an essential part of the complete stack for operational ML,” said Mike Del Balso, co-founder and CEO of Tecton. Tecton, San Francisco, California.

Sign up. Type: All Select type. All Sources Forks Tecton.ai has announced that it has received $25 million in seed and Series A funding co-led by Andreessen Horowitz and Sequoia. It has emerged from stealth and formally launched with its data platform for machine learning.
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Tecton's Feature Store manages the complete machine learning feature For a custom, private contract, please contact hello@tecton.ai for a private offer.

The startup sells a feature store, a repository to store and manage machine learning features and run data pipelines to transform raw data Tecton’s total funding is now at $60 million, with the recent funding aimed at accelerating product innovation and go-to-market activities. ML in production “Based on our experience building Uber Michelangelo, we know that feature stores are an essential part of the complete stack for operational ML,” said Mike Del Balso, co-founder and CEO of Tecton. Tecton, San Francisco, California.

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Tecton.ai has announced that it has received $25 million in seed and Series A funding co-led by Andreessen Horowitz and Sequoia. It has emerged from stealth and formally launched with its data platform for machine learning. Both Martin Casado, general partner at Andreessen Horowitz, and Matt Miller, partner at Sequoia, have joined the board.

Tecton is an Enterprise Feature Store. It empowers data scientists and engineers to productionize, share, monitor, and serve features.

Website. www.tecton.ai. Ownership Status. Privately Held (backing). Financing Status. Venture Capital-Backed. Primary Industry. Business/Productivity Software.

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Join us for this unique opportunity to get hands-on experience with the creators of Tecton's data platform and learn how you can leverage their tool to build a library of great features and serve them in Machine Learning Systems at scale. read more 2021-03-31 2020-12-09 A free virtual event on data engineering for applied Machine Learning. apply() is an 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.