real-time – Andrew Fairless, Ph.D.

What I Read: Feature Platforms

By Andrew Fairless on March 14, 2023February 4, 2023

https://huyenchip.com//2023/01/08/self-serve-feature-platforms.html Self-serve feature platforms: architectures and APIsChip HuyenJan 8, 2023 “The last few years saw the maturation of a core component of the MLOps stack that has significantly improved theContinue readingWhat I Read: Feature Platforms

What I Read: Realtime User Actions in Recommendation

By Andrew Fairless on February 27, 2023January 9, 2023

https://medium.com/pinterest-engineering/how-pinterest-leverages-realtime-user-actions-in-recommendation-to-boost-homefeed-engagement-volume-165ae2e8cde8 How Pinterest Leverages Realtime User Actions in Recommendation to Boost Homefeed Engagement VolumeXue Xia, Software Engineer, Homefeed Ranking; Neng Gu, Software Engineer, Content & User Understanding; Dhruvil Deven Badani,Continue readingWhat I Read: Realtime User Actions in Recommendation

What I Read: Realtime ML

By Andrew Fairless on February 16, 2023December 16, 2022

https://fennel.ai/blog/seven-reasons-why-realtime-ml-is/ Seven Reasons Why Realtime ML Is Here To StayNikhil GargJune 17, 2022 “…more and more top tech companies are making a larger part of their machine learning as realtimeContinue readingWhat I Read: Realtime ML

What I Read: Realtime ML Pipelines

By Andrew Fairless on February 1, 2023December 4, 2022

https://medium.com/@nparsons08/challenges-of-building-realtime-ml-pipelines-4782181425c7 Challenges of Building Realtime ML PipelinesNick ParsonsNov 18 “…as companies start introducing realtime into their ML pipelines, they are finding themselves having to weigh the trade-offs between performance, cost,Continue readingWhat I Read: Realtime ML Pipelines

What I Read: streaming for data scientists

By Andrew Fairless on September 21, 2022August 22, 2022

https://huyenchip.com//2022/08/03/stream-processing-for-data-scientists.html Introduction to streaming for data scientistsChip HuyenAug 3, 2022 “In our recent survey, almost half of the data scientists we asked said they would like to move from batchContinue readingWhat I Read: streaming for data scientists

What I Read: data replication in production

By Andrew Fairless on July 25, 2022June 27, 2022

https://medium.com/shippeo-tech-blog/debezium-to-snowflake-lessons-learned-building-data-replication-in-production-a5430a9fe85b Debezium to Snowflake: Lessons learned building data replication in productionOmar GhalawinjiJun 1 “We use Debezium, an excellent open-source tool to perform log-based Change Data Capture; which is the processContinue readingWhat I Read: data replication in production

What I Read: Machine learning is going real-time

By Andrew Fairless on March 3, 2021March 3, 2021

https://huyenchip.com/2020/12/27/real-time-machine-learning.html Machine learning is going real-timeDec 27, 2020Chip Huyen “Machine learning is going real-time, whether you’re ready or not. While the majority of companies are still debating whether there’s valueContinue readingWhat I Read: Machine learning is going real-time

What I Read: Architectures for Modern Data Infrastructure

By Andrew Fairless on February 4, 2021January 10, 2021

https://a16z.com/2020/10/15/the-emerging-architectures-for-modern-data-infrastructure/ Emerging Architectures for Modern Data Infrastructureby Matt Bornstein, Martin Casado, and Jennifer Li “We’re now starting to see the rise of massive, complex systems built around data – whereContinue readingWhat I Read: Architectures for Modern Data Infrastructure

What I Read: ML models in production

By Andrew Fairless on December 27, 2020December 20, 2020

https://medium.com/analytics-and-data/overview-of-the-different-approaches-to-putting-machinelearning-ml-models-in-production-c699b34abf86 Overview of the different approaches to putting Machine Learning (ML) models in productionJulien KervizicApr 29, 2019 “There are different approaches to putting models into productions, with benefits that canContinue readingWhat I Read: ML models in production

Tag: real-time