Year: 2021

What I Read: Improving a Machine Learning System (Part 1 – Broken Abstractions)

https://danshiebler.com/2021-11-06-ml-systems-1/ Improving a Machine Learning System (Part 1 – Broken Abstractions)Dan ShieblerPosted on November 6, 2021 “Making measurable improvements to a mature machine learning system is extremely difficult. In thisContinue readingWhat I Read: Improving a Machine Learning System (Part 1 – Broken Abstractions)

What I Read: From Data Engineer to SysAdmin: Put down the K8s cluster

https://thundergolfer.com/kubernetes/infrastructure/data-engineering/2021/11/04/from-data-eng-to-sys-admin-put-down-k8s/ From Data Engineer to SysAdmin: Put down the K8s cluster, your pipelines can run without itJonathon BelottiNov 4, 2021 “Now this is like the thousandth ‘beware K8s’ post, andContinue readingWhat I Read: From Data Engineer to SysAdmin: Put down the K8s cluster

What I Read: Deep Learning Optimization Theory

https://towardsdatascience.com/deep-learning-optimization-theory-introduction-148b3504b20f?gi=ff0bd10cc9fe Deep Learning Optimization Theory — IntroductionUnderstanding the theory of optimization in deep learning is crucial to enable progress. This post introduces the experimental and theoretical approaches to studying it.OmriContinue readingWhat I Read: Deep Learning Optimization Theory

What I Read: Non-Technical Guide to Interpreting SHAP

https://www.aidancooper.co.uk/a-non-technical-guide-to-interpreting-shap-analyses/ Explaining Machine Learning Models: A Non-Technical Guide to Interpreting SHAP AnalysesAidan CooperNov 1, 2021With interpretability becoming an increasingly important requirement for machine learning projects, there’s a growing need forContinue readingWhat I Read: Non-Technical Guide to Interpreting SHAP