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Presentation: Deep Learning for Application Performance Optimization

Track: Practical Machine Learning

Location: Empire Complex, 7th fl.

Duration: 10:35am - 11:25am

Day of week: Wednesday

Slides: Download Slides

Level: Intermediate - Advanced

Persona: Developer, Developer, JVM

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Application performance has direct impact on business and scaling ability. Performance tuning usually involves periodically setting a number of parameters that control run-time environment including CPU, memory, threading, garbage collection, etc.

In this session we present our experience and best practice for autonomous, continuous application performance tuning using deep learning.  The participants will learn how to build deep learning models in order to model the application performance for various configuration settings.  A case study will be based on tuning the Java virtual machine for enterprise applications.

Speaker: Zoran Sevarac

Java and Neural Network Expert, Creator @Neuroph, & Founder @DeepNetts

Zoran Sevarac is software developer, AI researcher, entreprenuer and university professor.  He works at AI Lab at University of Belgrade, and he is CEO of deep learning startup Deep Netts. He is a founder of popular open source educational neural network software Neuroph, which has won prestigious Duke Choice Award. He is a member of Java Champions program and JCP Expert group for visual recognition. His main interests include software engineering, Java, machine learning and deep learning.

Find Zoran Sevarac at