Data Engineering Infrastructure Presentation Tuning 
InfoQ
MAY 8, 2024
Jules Damji discusses which infrastructure should be used for distributed fine-tuning and training, how to scale ML workloads, how to accommodate large models, and how can CPUs and GPUs be utilized? By Jules Damji
Dynatrace
JULY 6, 2022
With ever-evolving infrastructure, services, and business objectives, IT teams can’t keep up with routine tasks that require human intervention. Automating IT practices without integrated AIOps presents several challenges. This requires significant data engineering efforts, as well as work to build machine-learning models.
The Netflix TechBlog
DECEMBER 21, 2020
This article will list some of the use cases of AutoOptimize, discuss the design principles that help enhance efficiency, and present the high-level architecture. Some of the optimizations are prerequisites for a high-performance data warehouse. Orient: Gather tuning parameters for a particular table that changed.
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