Explore deep learning concepts and their practical implementation in this Spring I/O 2017 conference talk. Begin with an overview of recent advancements in deep learning before delving into DeepLearning4J, an open-source, commercial-grade deep learning library for Java. Discover how to integrate neural networks into Spring Boot applications and learn to create a supervised learning system using Spring Boot Actuator. Gain insights into topics such as computational filters, complexity optimization, training vs. testing, implicit parameters, and ImageNet. Understand the motivations behind deep learning for Java and receive recommendations for implementing these technologies in your own projects.
Overview
Syllabus
Intro
Unit Cell
Applications
Computational Filters
Dependence
Complexity
Optimization
Training vs Test
Implicit Parameters
ImageNet
DeepLearning4J
Learning for Java
Deep Learning for Java
Spring Boot Actuator
Custom Actuator
Strategy
Approach
Motivations
Recommendations
Taught by
Spring I/O
