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BU BÖLÜM HAKKINDA
Paychex’s goal of providing the best user experience for our clients has led to a significant investment in performance testing and monitoring of our applications. Currently all Paychex applications record the execution time for every task and subtask to logs. These are indexed by Splunk, allowing us to identifying areas where changes to code and database queries will have a positive impact on the overall user experience. This presentation will focus on combining this user experience data with client demographic data (such as the number of active employees) and using the Splunk Machine Learning Toolkit to build predictive models of user experience based on client demographic data.
Speaker(s)
Ken Tupper, Lead Performance Engineer, Paychex
Slides PDF link - https://conf.splunk.com/files/2019/slides/FN1631.pdf?podcast=1577146203
Product: Splunk Machine Learning Toolkit, AI/ML
Track: Foundations/Platform
Level: Intermediate
ingilizce
Amerika Birleşik Devletleri
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Feragatname: Bu sayfaya yerleştirilmiş podcast ve sanat eserleri, sahibinin mülkiyetinde olan ve Listen Notes, Inc.'e bağlı olmayan veya tarafından onaylanmayan Splunk'e aittir.
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