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UID:01a1989d-2ca3-7040-97a7-c9ea6e58e13b@www.devopschat.co
DTSTAMP:20261106T124533Z
DTSTART:20200428T160000Z
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SUMMARY:Software Engineering for ML-Enabled Systems
DESCRIPTION:In this talk\, Christian Kaestner will give an overview of the 
 challenges of building software systems with ML components and challenges 
 of how data scientists and software engineers need to work together. Data 
 scientists often focus on producing a model and measuring accuracy\, but w
 hen the end goal is to build production systems\, the model is often only 
 one component in a larger software system. In production systems\, quality
  is measured usually not in terms of model accuracy but in terms of the ov
 erall experience among the system's users. Many new challenges arise often
  ignored when just focusing on building ML models in a notebook\, such as 
 resource consumption and scalability\, gathering data at scale\, deploying
  models\, regularly retraining models\, and detecting feedback loops. Whil
 e machine learning raises new challenges\, software engineers have signifi
 cant expertise to offer with regard to requirements\, design\, architectur
 e\, deployment\, and quality assurance\, drawing on decades of experience 
 and methods for building systems that scale and are responsive and robust\
 , even when built on unreliable components. Christian will make a case for
  a software engineering mindset\, and dive a little deeper into the qualit
 y assurance of ML-enabled systems (testing the pipeline\, testing in produ
 ction\, telemetry design) as one example.\n\nSlides: https://ckaestne.gith
 ub.io/seai/F2019/slides/talks/code_supply2020/cs.html\n\nChristian Kaestne
 r is an associate professor at Carnegie Mellon University in the area of s
 oftware engineering. His research has traditionally focused on quality ass
 urance for highly-configurable systems\, but more recently his interests i
 nclude sustainability and stress in open source communities and software e
 ngineering for AI-enabled systems. He has recently designed a class on lat
 ter topic in which he looks at building intelligent systems from a softwar
 e engineering lense (requirements\, design\, quality assurance\, deploymen
 t\, process\, ...): https://ckaestne.github.io/seai/\n\n==================
 ==\n\nWe'll be using https://8x8.vc for conferencing. No account is necess
 ary but it is recommended. To test your system\, create a free conference 
 there or at https://meet.jit.si\, as they use the same technology. Those o
 n mobile devices will need to install the 8x8 Video Conference app.\n\nhtt
 ps://www.devopschat.co/meetings/software-engineering-for-ml-enabled-system
 s
URL:https://www.devopschat.co/meetings/software-engineering-for-ml-enabled-
 systems
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