All Resources

Webinar: Supercharging Recommendation Systems With Generative AI & Real-Time Context

Join Tecton Travel (our fictitious travel company) as it builds an enhanced recommendation system with Generative AI to increase bookings on its website.

VideosOperational & Real-Time MLRecommender Systems

Batch, Streaming & Real-Time Data: How to Leverage Their Full Power for Production ML

Today, the data flows for ML applications are more complex and varied than ever. To gain a competitive edge, businesses are increasingly including online models in their products or real-time processes, introducing a new range of operational concerns—and often, an explosion in the number of data sources and transformations used by their ML models.

Ebooks & WhitepapersOperational & Real-Time ML

Building Plaid’s ML Fraud Detection Application, Signal

Watch this virtual fireside chat to explore best practices in designing and deploying ML fraud detection applications.

VideosCustomer Stories

apply(ops)

This series focuses on platforms and architectures for production machine learning projects. Practitioners share best practices and lessons learned when designing machine learning systems.

VideosOperational & Real-Time ML

Orchestrating Feature Pipelines: Announcing the Tecton Airflow Provider

The Tecton Airflow provider allow feature platform orchestration through the management of Tecton Feature Views and Feature Services in Airflow.

PostsPartners & Integrations

Combining Online Stores for Real-Time Serving

Tecton uses Redis or DynamoDB as an online store for production machine learning. This post provides examples that use both databases together

PostsFeature PlatformsTutorials

apply(risk): ML Data Engineering for Risk & Fraud Detection

Watch the replays from companies like Remitly, Block, Affirm, and more!

VideosFraud DetectionOperational & Real-Time ML

Webinar: Creating Better Machine Learning Features for Real-Time Decisions

A machine learning model can only be as good as the features that power it.  The challenge, however, is that ML models require high-quality data that can be difficult to process and serve in production.  Transforming data into features that …

VideosFeature PlatformsOperational & Real-Time ML

The State of Applied Machine Learning 2023

We surveyed over 1700 ML practitioners for this inaugural report on the state of applied machine learning. It provides a comprehensive overview of applied ML, and shares the challenges and opportunities in the space, along with common trends across …

Ebooks & WhitepapersOperational & Real-Time ML

Virtual Hands-On Lab: Building a Feature Pipeline

Through a series of code examples, we’ll walk through the concepts and code that will help you build a modern technical architecture that simplifies the process of managing production ML models and features.

VideosTutorials

Breaking Out of the Training Data Bottleneck: How to Generate High-Quality Data, Faster

In machine learning, it's known that you can’t create a great model without great training data. You need to train your ML models the right way, with the right data, in order to get accurate predictive outputs.

Ebooks & Whitepapers

Discover how FanDuel built a powerful ML platform for personalized experiences

Learn how FanDuel engineered and built a powerful ML Platform to deliver personalized experiences to their users.

VideosCustomer StoriesFeature Platforms