MLOps – Page 4 – Andrew Fairless, Ph.D.

What I Read: Real World Recommendation System

By Andrew Fairless on May 25, 2022April 25, 2022

https://blog.fennel.ai/p/real-world-recommendation-system?s=r Real World Recommendation System – Part 1Nikhil GargApr 10 “Training a collaborative filtering based recommendation system on a toy dataset is a sophomore year project in colleges these days.Continue readingWhat I Read: Real World Recommendation System

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: Maps of Model Space, Stan

By Andrew Fairless on January 5, 2022December 11, 2021

https://statmodeling.stat.columbia.edu/2021/11/19/drawing-maps-of-model-space-with-modular-stan/ Drawing Maps of Model Space with Modular StanPosted on November 19, 2021 9:50 AM by AndrewThis post is by Ryan Bernstein. “What if instead of describing one model atContinue readingWhat I Read: Maps of Model Space, Stan

What I Read: AntiPatterns, MLOps

By Andrew Fairless on January 4, 2022December 11, 2021

https://arxiv.org/abs/2107.00079 Using AntiPatterns to avoid MLOps MistakesNikhil Muralidhar, Sathappah Muthiah, Patrick Butler, Manish Jain, Yu Yu, Katy Burne, Weipeng Li, David Jones, Prakash Arunachalam, Hays ‘Skip’ McCormick, Naren Ramakrishnan “HereContinue readingWhat I Read: AntiPatterns, MLOps

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: 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 Read: Systems for Machine Learning

By Andrew Fairless on September 14, 2021August 20, 2021

https://thegradient.pub/systems-for-machine-learning/ Systems for Machine LearningKabir Nagrecha14.Aug.2021 “Machine learning’s increasing importance to real-world applications brought awareness of a new field focused on ML in practice – machine learning systems (or, asContinue readingWhat I Read: Systems for Machine Learning

What I Read: The one data platform to rule them all

By Andrew Fairless on August 26, 2021August 17, 2021

https://leighmariebraswell.substack.com/p/the-one-data-platform-to-rule-them The one data platform to rule them all… but according to whom?An overview of recent data startups based on popular end usersLeigh Marie BraswellJul 20 “…seeing so many “dataContinue readingWhat I Read: The one data platform to rule them all

What I Read: What I’ve learned about MLOps

By Andrew Fairless on June 23, 2021June 7, 2021

https://ramseyelbasheer.io/2021/05/17/what-ive-learned-about-mlops-from-speaking-with-100-ml-practitioners/ What I’ve learned about MLOps from speaking with 100+ ML practitionersby Ramsey ElbasheerMay 17, 2021 “Without further ado, here is part of the key takeaways around the everyday MLOpsContinue readingWhat I Read: What I’ve learned about MLOps

What I Read: Productizing Machine Learning Models

By Andrew Fairless on June 14, 2021May 30, 2021

https://blog.sasken.com/productizing-machine-learning-models-an-introduction Productizing Machine Learning Models – An IntroductionFeb 11, 2020 4:36:36 AM “This post will explore some of the challenges in placing ML models in a production environment. It willContinue readingWhat I Read: Productizing Machine Learning Models

Tag: MLOps