feature store – Andrew Fairless, Ph.D.

What I Read: Unify Batch and ML Systems

By Andrew Fairless on January 18, 2024November 7, 2023

https://www.kdnuggets.com/2023/09/hopsworks-unify-batch-ml-systems-feature-training-inference-pipelines Unify Batch and ML Systems with Feature/Training/Inference PipelinesBy Jim Dowling, Co-Founder & CEO, HopsworksSeptember 27, 2023 “This article introduces a unified architectural pattern for building both Batch and Real-TimeContinue readingWhat I Read: Unify Batch and ML Systems

What I Read: MLOps, Data Engineering

By Andrew Fairless on May 18, 2023May 1, 2023

https://www.cpard.xyz/posts/mlops_is_mostly_data_engineering/ MLOps is Mostly Data Engineering.22 March 2023Kostas Pardalis “The question here is… why do we need a whole new category of products?… The true need here is developer toolingContinue readingWhat I Read: MLOps, Data Engineering

What I Read: end-to-end, infrastructure, recommendations

By Andrew Fairless on November 7, 2022September 27, 2022

Recommend API Recommend APIUnified end-to-end machine learning infrastructure to generate recommendationsKatrina Ni Senior Software Engineer, Machine LearningAaron Maurer Senior Manager, Software EngineeringSeptember 6, 2022 “…we developed a unified framework weContinue readingWhat I Read: end-to-end, infrastructure, recommendations

What I Read: Bundling into the Database

By Andrew Fairless on July 5, 2022June 27, 2022

https://www.ethanrosenthal.com/2022/05/10/database-bundling/ Let’s Continue Bundling into the DatabaseEthan RosenthalMay 10, 2022 “Truthfully, I just want to argue that feature stores, metrics layers, and machine learning monitoring tools are all abstraction layersContinue readingWhat I Read: Bundling into the Database

What I Read: marketplace ranking infrastructure

By Andrew Fairless on March 15, 2022January 20, 2022

https://craft.faire.com/building-faires-new-marketplace-ranking-infrastructure-a53bf938aba0 Building Faire’s new marketplace ranking infrastructureSam KennyNov 3, 2021 “At Faire, all three of these core surfaces are powered by one unified ranking infrastructure that we refer to internallyContinue readingWhat I Read: marketplace ranking infrastructure

What I Read: Real-time machine learning

By Andrew Fairless on March 9, 2022January 20, 2022

https://huyenchip.com//2022/01/02/real-time-machine-learning-challenges-and-solutions.html Real-time machine learning: challenges and solutionsJan 2, 2022 • Chip Huyen “Starting with a batch prediction system, we’ll discuss what’s needed for a simple online prediction system using batchContinue readingWhat I Read: Real-time machine learning

What I Read: Improving a Machine Learning System (Part 2 – Features)

By Andrew Fairless on December 27, 2021November 16, 2021

https://danshiebler.com/2021-11-09-ml-systems-2/ Improving a Machine Learning System (Part 2 – Features)Dan ShieblerPosted on November 9, 2021 “…one of the most important parts of improving a machine learning system is improving theContinue readingWhat I Read: Improving a Machine Learning System (Part 2 – Features)

What I Read: Lessons on ML Platforms

By Andrew Fairless on December 20, 2021November 16, 2021

https://towardsdatascience.com/lessons-on-ml-platforms-from-netflix-doordash-spotify-and-more-f455400115c7 Lessons on ML Platforms — from Netflix, DoorDash, Spotify, and moreErnest ChanMay 12 “Many companies who do ML well have invested in ML platforms to enable data scientists toContinue readingWhat I Read: Lessons on ML Platforms

What I Read: Building Data Platform

By Andrew Fairless on August 12, 2021July 22, 2021

https://www.montecarlodata.com/the-quick-and-dirty-guide-to-building-your-data-platform/ Updated July 9, 2021The Quick and Dirty Guide to Building Your Data PlatformBarr Moses, Lior Gavish“For most organizations, building a data platform is no longer a nice-to-have but aContinue readingWhat I Read: Building Data Platform

What I Read: Feature stores

By Andrew Fairless on May 31, 2021May 14, 2021

https://www.kdnuggets.com/2021/05/feature-stores-how-avoid-feeling-every-day-is-groundhog-day.html Feature stores – how to avoid feeling that every day is Groundhog DayBy Monte Zweben, CEO, Splice Machine. “Feature stores stop the duplication of each task in the MLContinue readingWhat I Read: Feature stores

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