In This Week in Machine Learning podcast, Xavier Amatriain from Quora discusses the process of engineering practical machine learning systems. Amatriainis a former machine learning researcher who went on to lead the recommender systems team at Netflix, and is now the vice president of engineering at Quora, the Q&A site. “What the heck is a multi-arm bandit and how can it help us.”
Video: System Methodology—Holistic Performance Analysis on Modern Systems
August 26, 2016 by
“This talk will discuss various system performance issues, and the methodologies, tools, and processes used to solve them. The focus is on single systems (any operating system), including single cloud instances, and quickly locating performance issues or exonerating the system. Many methodologies will be discussed, along with recommendations for their implementation, which may be as documented checklists of tools, or custom dashboards of supporting metrics. In general, you will learn to think differently about your systems, and how to ask better questions.”
Video: Brendan Gregg Looks at Tools & Methodologies for Linux System Performance
May 6, 2016 by
In this video from the 2016 Percona Data Performance Conference, Brendan Gregg, Senior Performance Architect from Netflix presents: Linux Systems Performance. “Systems performance provides a different perspective for analysis and tuning, and can help you find performance wins for your databases, applications, and the kernel. However, most of us are not performance or kernel engineers, […]
Video: Brendan Gregg Tutorial on Linux Performance Tools
August 6, 2015 by
In this video from the Velocity 2015 conference, Brendan Gregg from Netflix presents a 90 minute tutorial on Linux performance tools. “There are many performance tools nowadays for Linux, but how do they all fit together, and when do we use them? I’ve spoken on this topic before, but given a 90 minute time slot I was able to include more methodologies, tools, and live demonstrations, making it the most complete tour of the topic I’ve done.”
