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Our thoughts on extracting ML signal from the data noise
What is a Feature Store?
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Announcing Feast 0.10
Today, we’re announcing Feast 0.10, an important milestone towards our vision for a lightweight feature store. Feast is an open source feature store that helps you serve features in production. It prevents feature leakage by building training datasets from your … Read More
How to Build a Fraud Model with a Feature Store
Many companies with platforms that involve financial transactions are looking to bring them in-house to some degree as they can have more control over the user experience and usually save money on transaction fees over outsourced solutions. While the advantages … Read More
Announcing apply()’s Speaker Lineup
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 … Read More
How Machine Learning Teams Share and Reuse Features
What does an “ML-enabled” company look like? The companies that come to mind, like Uber, Twitter, or Google, have tens of thousands of machine learning (ML) models in production. They use these models to make intelligent predictions across the business … Read More
Data Software-as-a-Service: The Case for a Hybrid Deployment Architecture
Lior Gavish & Kevin Stumpf As founders of companies that build solutions designed to help teams deliver on the promise of data, we knew we wanted to build great products that are easy to deploy and manage for our customers. … Read More
Tide Deploys Models 2x Faster with Tecton
50% improvement Time to deploy new models to production decreased to just 1 month from 2 – 4 months. 9 months Engineering time recovered from continuing to build internal feature store. 3 engineers Resources repurposed from maintaining internal feature store. … Read More
Atlassian Deploys New Features in 1 Day with Tecton
200k Customer interactions improved per day 1 Day Time to build and deploy new features 2-3 Engineers Resources repurposed from maintaining internal feature store Atlassian builds tools that help teams collaborate and create together, including Jira Software and Confluence. To … Read More
Amazon SageMaker and Tecton: How to Choose the Right Feature Store on AWS
Amazon recently introduced SageMaker Feature Store, recognizing that one of the largest challenges facing data science teams is building and serving high-quality machine learning features both in training and in production. The team at Tecton could not agree more with … Read More
Feature Store in General Availability & Series B Funding
Today marks a big milestone for Tecton. We’re excited to announce that the Tecton feature store is now in General Availability, and that we have raised $35 Million in Series B funding from our existing lead investors, Andreessen Horowitz and … Read More
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