deployment – Page 5 – Andrew Fairless, Ph.D.

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 dysfunctions of Data Engineering

By Andrew Fairless on September 9, 2021August 20, 2021

https://medium.com/@mrtrustworthy/from-data-driven-to-driving-data-the-dysfunctions-of-data-engineering-34c34496ed8e From Data Driven to Driving Data— The dysfunctions of Data EngineeringMrTrustworthyJul 27 “Being Data Driven isn’t enough…. We need Data Engineering… as a methodical approach at re-designing how aContinue readingWhat I Read: The dysfunctions of Data Engineering

What I Read: Machine Learning, Rendezvous Architecture

By Andrew Fairless on September 8, 2021August 17, 2021

https://www.saigeetha.in/post/machine-learning-rendezvous-architecture Machine Learning – Rendezvous ArchitectureSai Geetha M N “The Rendezvous architecture proposed by Ted Dunning and Ellen Friedman in their book on Machine Learning Logistics was a wonderful solutionContinue readingWhat I Read: Machine Learning, Rendezvous Architecture

What I Read: I Like Notebooks

By Andrew Fairless on August 17, 2021July 22, 2021

https://youtu.be/9Q6sLbz37gk I Like NotebooksOct 28, 2020Jeremy Howard “I like using Jupyter Notebooks… Particularly when combined with nbdev… In this video, I explain why, and explain why I have a differentContinue readingWhat I Read: I Like Notebooks

What I Read: Building Data Platform

By Andrew Fairless on August 12, 2021July 22, 2021

https://www.montecarlodata.com/the-quick-and-dirty-guide-to-building-your-data-platform/ Updated July 9, 2021The Quick and Dirty Guide to Building Your Data PlatformBarr Moses, Lior Gavish“For most organizations, building a data platform is no longer a nice-to-have but aContinue readingWhat I Read: Building Data Platform

What I Read: What is a Data Mesh?

By Andrew Fairless on July 6, 2021June 22, 2021

https://cnr.sh/essays/what-the-heck-data-mesh What the Heck is a Data Mesh?!Chris Riccomini on June 8, 2021 “Yet, organizations don’t think of data as a product…. It would be madness to propose centralizing allContinue readingWhat I Read: What is a Data Mesh?

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: Hiring Data Scientists

By Andrew Fairless on June 21, 2021June 7, 2021

https://towardsdatascience.com/stop-hiring-data-scientists-improve-ml-product-team-retention-8ae04dac406e?gi=175fec4d5962 Stop (and Start) Hiring Data ScientistsThree “stop & start” tactics to improve talent retentionIan XiaoMay 14 “… we’ve been overly spotlighting the algorithmic work and success of data scienceContinue readingWhat I Read: Hiring Data Scientists

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

What I Read: Accelerating ML within CNN

By Andrew Fairless on June 3, 2021May 14, 2021

https://medium.com/cnn-digital/accelerating-ml-within-cnn-983f6b7bd2eb Accelerating ML within CNNKelly DavisMay 11 “Unfortunately, it was not designed for lightweight experimentation, and because of that, the research iteration process was frustratingly slow… we explored a numberContinue readingWhat I Read: Accelerating ML within CNN

Tag: deployment