Overview
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Explore the modeling of stochastic failure behavior in telecommunications and IT systems through machine learning in this conference talk from code::dive 2022. Delve into corrective maintenance strategies and conventional methods before embarking on a comprehensive roadmap for implementing data-driven solutions. Learn about designing data collection systems, configuring Prometheus, and working with log files. Examine various data visualization techniques, including histograms and boxplots, to gain insights into system behavior. Discover the goals of estimation and how neural networks can be applied to failure prediction. Gain practical knowledge through code examples and real-world results. Investigate the Shop Library and Waterfall Modeling techniques, and familiarize yourself with essential mathematical terms, sets, and indices used in stochastic modeling. Presented by Sadegh Karimi, an experienced telecommunications professional from Nokia R&D center in Poland, this talk offers valuable insights for those looking to leverage AI and machine learning in the telco industry.
Syllabus
Introduction
Corrective Maintenance
Conventional Method
Roadmap
Data Collection System Design
Prometheus
Configuration
Log File
Features
Histogram
Boxplot
Histograms
Plot
Goal of estimation
Neural network
Neural network code
Results
Shop Library
Waterfall
Modeling
Mathematical terms
Sets and indices
Code
Result
Taught by
code::dive conference