data engineering – Page 11 – Andrew Fairless, Ph.D.

What I Read: Maintaining Machine Learning in Production

By Andrew Fairless on January 19, 2021December 27, 2020

https://eugeneyan.com/writing/practical-guide-to-maintaining-machine-learning/ A Practical Guide to Maintaining Machine Learning in Production “This follow-up will share some practices I’ve found useful to maintaining machine learning in production. They are: Monitor Training andContinue readingWhat I Read: Maintaining Machine Learning in Production

What I Read: Data Scientists Should Be More End-to-End

By Andrew Fairless on January 17, 2021December 26, 2020

https://eugeneyan.com/writing/end-to-end-data-science/ Unpopular Opinion – Data Scientists Should Be More End-to-End “Eric Colson of Stitch Fix was initially “lured to a function-based division of labour by the attraction of process efficiencies”…Continue readingWhat I Read: Data Scientists Should Be More End-to-End

What I Read: Intro to Data Engineering for Data Scientists

By Andrew Fairless on January 12, 2021December 23, 2020

https://towardsdatascience.com/intro-to-data-engineering-for-data-scientists-fa6c864a3ecc?gi=dd86c8bdeaa0 Intro to Data Engineering for Data ScientistsAn overview of data infrastructure which is frequently asked during interviewsWei WangJul 19 “…I have found that fresh data science graduates often don’tContinue readingWhat I Read: Intro to Data Engineering for Data Scientists

What I Read: Making Netflix’s Data Infrastructure Cost-Effective

By Andrew Fairless on January 11, 2021December 23, 2020

https://netflixtechblog.com/byte-down-making-netflixs-data-infrastructure-cost-effective-fee7b3235032?gi=dda98a1395a9 Byte Down: Making Netflix’s Data Infrastructure Cost-EffectiveNetflix Technology BlogJul 8 · 8 min readBy Torio Risianto, Bhargavi Reddy, Tanvi Sahni, Andrew Park “At many other organizations, an effective wayContinue readingWhat I Read: Making Netflix’s Data Infrastructure Cost-Effective

What I Read: Running Machine Learning at Scale

By Andrew Fairless on January 7, 2021December 23, 2020

https://medium.com/@jrodthoughts/some-things-uber-learned-from-running-machine-learning-at-scale-70dccdfb944d Some Things Uber Learned from Running Machine Learning at ScaleUber machine learning runtime Michelangelo has been in operation for a few years. What has the Uber team learned?Jesus RodriguezJulContinue readingWhat I Read: Running Machine Learning at Scale

What I Read: DevOps for ML Data

By Andrew Fairless on December 23, 2020December 10, 2020

https://tecton.ai/blog/devops-ml-data/ Why We Need DevOps for ML DataPosted by Kevin Stumpf on April 28, 2020 “Unfortunately, most tools under the MLOps banner tend to focus only on workflows around theContinue readingWhat I Read: DevOps for ML Data

Tag: data engineering