continuous delivery – Andrew Fairless, Ph.D.

What I Read: Modern Stack for ML Infrastructure

By Andrew Fairless on June 13, 2022May 23, 2022

https://youtu.be/gZnhSHvhuFQThe Modern Stack for ML Infrastructure | OuterboundsMay 2, 2022Data Council “Metaflow was originally developed at Netflix to provide a user-friendly platform for a wide range of ML use cases…Continue readingWhat I Read: Modern Stack for ML Infrastructure

What I Read: MLOps Documentation

By Andrew Fairless on February 2, 2022January 20, 2022

https://www.kdnuggets.com/2021/12/best-practices-mlops-docs.html Best Practices for MLOps DocumentationBy Nifesimi Ademoye “Why does technical documentation matter in MLOps?…. MLOps levels are defined by the extent of automation of processes in an ML pipeline,Continue readingWhat I Read: MLOps Documentation

What I Read: The Uselessness of Useful Knowledge

By Andrew Fairless on November 2, 2021October 24, 2021

https://www.quantamagazine.org/science-has-entered-a-new-era-of-alchemy-good-20211020/ The Uselessness of Useful KnowledgeRobbert DijkgraafOctober 20, 2021Today’s powerful but little-understood artificial intelligence breakthroughs echo past examples of unexpected scientific progress.“…the current state of AI research is nothing newContinue readingWhat I Read: The Uselessness of Useful Knowledge

What I Watch: Continuous Integration vs Feature Branch Workflow

By Andrew Fairless on June 1, 2021May 14, 2021

https://youtu.be/v4Ijkq6Myfc Continuous Integration vs Feature Branch WorkflowJan 6, 2021Continuous Delivery “Continuous Integration and Feature Branching are both very popular ways of organising work in a development team, but they areContinue readingWhat I Watch: Continuous Integration vs Feature Branch Workflow

What I Read: End-to-End Machine Learning Platforms

By Andrew Fairless on January 15, 2021December 24, 2020

https://databaseline.tech/a-tour-of-end-to-end-ml-platforms/ A Tour of End-to-End Machine Learning PlatformsIan Hellström21 February 2020 “What turns a collection of machine learning solutions into an end-to-end machine learning platform is an architecture that embracesContinue readingWhat I Read: End-to-End Machine Learning Platforms

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

What I Read: Monitoring Machine Learning Models in Production

By Andrew Fairless on December 20, 2020December 23, 2020

https://christophergs.com/machine%20learning/2020/03/14/how-to-monitor-machine-learning-models/ Monitoring Machine Learning Models in ProductionA Comprehensive Guide14 March 2020 “Once you have deployed your machine learning model to production it rapidly becomes apparent that the work is notContinue readingWhat I Read: Monitoring Machine Learning Models in Production

Tag: continuous delivery