MLOps – Page 3 – Andrew Fairless, Ph.D.

What I learn: How, learn machine learning

By Andrew Fairless on January 18, 2023December 4, 2022

https://vickiboykis.com/2022/11/10/how-i-learn-machine-learning/ How I learn machine learningVicki BoykisNov 10 2022 “My overarching goal as an MLE is to continuously work towards designing and deploying well-designed, and transparent machine learning systems andContinue readingWhat I learn: How, learn machine learning

What I Read: The Farama Foundation

By Andrew Fairless on December 22, 2022November 5, 2022

https://farama.org/Announcing-The-Farama-Foundation Announcing The Farama FoundationThe future of open source reinforcement learning25 October 2022 “This means that the barrier to reinforcement learning seeing widespread deployment is a tooling problem…. Our grandContinue readingWhat I Read: The Farama Foundation

What I Read: Dev and Data Science Independence

By Andrew Fairless on December 13, 2022November 5, 2022

https://medium.com/riskified-technology/how-we-enabled-dev-and-data-science-independence-with-clear-api-boundaries-3a6a28597746 How We Enabled Dev and Data Science Independence With Clear API Boundaries Using Airflow and DatabricksUri BrodskyOct 18 “In this post, I will show you how we enabled ourContinue readingWhat I Read: Dev and Data Science Independence

What I Read: Productizing Large Language Models

By Andrew Fairless on November 16, 2022September 27, 2022

https://blog.replit.com/llms Productizing Large Language ModelsWed Sep 21 2022by Amjad Masad, Samip Dahal, Luis Héctor Chávez “Large Language Models (LLMs)… can chat, write poetry, write code, and even do basic arithmetic.Continue readingWhat I Read: Productizing Large Language Models

What I Read: ML Engineering

By Andrew Fairless on November 1, 2022September 26, 2022

https://www.shreya-shankar.com/phd-year-one/ Thoughts on ML Engineering After a Year of my PhDJuly 18, 2022Shreya Shankar “There are two types of business-critical MLEs. The first is the Task MLE…”

What I Read: Machine Learning Metadata

By Andrew Fairless on October 24, 2022September 9, 2022

https://www.kdnuggets.com/2022/08/machine-learning-metadata-store.html Machine Learning Metadata StoreBy Akruti Acharya, Technical Content WriterAugust 31, 2022 “Storing the metadata would help in retraining the same model and get the same results…. Hence, the needContinue readingWhat I Read: Machine Learning Metadata

What I Read: Is Data Scientist Still the Sexiest Job?

By Andrew Fairless on September 5, 2022August 3, 2022

https://hbr.org/2022/07/is-data-scientist-still-the-sexiest-job-of-the-21st-century Is Data Scientist Still the Sexiest Job of the 21st Century?Thomas H. Davenport and DJ PatilJuly 15, 2022 “Ten years ago we published the article “Data Scientist: Sexiest JobContinue readingWhat I Read: Is Data Scientist Still the Sexiest Job?

What I Read: Hidden Technical Debts

By Andrew Fairless on August 15, 2022July 18, 2022

https://www.kdnuggets.com/2022/07/hidden-technical-debts-every-ai-practitioner-aware.html Hidden Technical Debts Every AI Practitioner Should be Aware ofVidhi ChughJuly 7, 2022 “…technical debt is the long-term costs incurred by moving quickly in software engineering…. A large partContinue readingWhat I Read: Hidden Technical Debts

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: Deploying Deep Learning

By Andrew Fairless on June 28, 2022June 27, 2022

https://thegradient.pub/lessons-from-deploying-deep-learning-to-production/ Lessons From Deploying Deep Learning To ProductionPeter Gao16.May.2022 “I used to think that machine learning was about the models. Actually, machine learning in production is about pipelines.”

Tag: MLOps