Blog - Tecton



Welcome to the Tecton blog

Our thoughts on extracting ML signal from the data noise


Posted by  Mike Del Balso
October 20, 2020

What is a Feature Store?


apply(meetup): Announcing the Speaker Lineup for August 11

Here we go again! It seems like just yesterday we were hosting the first iteration of apply(). Now back by popular demand, we’re hosting apply(meetup) on August 11th from 9am to 12pm Pacific Time … Read More

Posted by  Tecton
July 20, 2021

apply() Highlight: How to Use Fast & Fresh Features for Online Predictions

Online inference can significantly increase the impact of a machine learning model by incorporating fresh data. For example, if we’re building product recommendations for an e-commerce site, our model will benefit from information about what other products the user recently … Read More

Posted by  Derek Salama
July 7, 2021

apply() Highlight: How Feature Logging Enables Real-Time ML

Generating training data for an online, real-time machine learning system can be tricky. In order to guard against temporal data leakage, training events must use only historical features that were valid as of that point in time. This requires effectively … Read More

Posted by  Matt Bleifer
June 17, 2021

Real-Time Aggregation Features for Machine Learning (Part 2)

In the following sections, we describe an approach to solving these challenges that we’ve proven out at scale at Tecton, and that has been used successfully in production at Airbnb and Uber for several years. The discussed approach explains Tecton’s implementation which relies entirely on open source technologies … Read More

Posted by  Kevin Stumpf
June 2, 2021

Real-Time Aggregation Features for Machine Learning (Part 1)

Machine Learning features are derived from an organization’s raw data and provide a signal to an ML model. A very common type of feature transformation is a rolling time window aggregation. For example, you may use the rolling 30-minute order count of a restaurant to predict the order preparation time of your favorite food delivery service … Read More

Posted by  Kevin Stumpf
June 2, 2021

apply() Conference Recap

Last month, on April 21 and 22, Tecton hosted apply(): the ML data engineering conference to share the latest best practices in ML data engineering. The conference brought together industry thought leaders and practitioners from over 30 leading organizations and … Read More

Posted by  Manmeet Gujral
May 25, 2021

Tecton Named Gartner Cool Vendor

We’re excited to announce that Tecton has been named a 2021 Gartner Cool Vendor in Enterprise AI Operationalization and Engineering(1). This is great recognition for Tecton’s vision of solving the data problem for ML by making feature stores accessible to … Read More

Posted by  Gaetan Castelein
May 18, 2021

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

Posted by  Willem Pienaar
April 15, 2021

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

Posted by  Jack Wells
April 5, 2021

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