Machine Learning for Java Developers Training

Machine learning gives computers the ability to learn to solve specific type of tasks without being explicitly programmed.

Machine Learning for Java Developers is a 2 day intensive training designed for Java development teams who want to add machine learning into their solutions. The training gives basic understanding of machine learning concepts and techniques,  and provides hands on exercises in Java code. An exercise during the training also includes a use case of your choice for applying machine learning, preferable related to some of the projects that you’re working on.

You will learn to:

  • Recognize problems and features that could benefit from machine learning
  • Design machine learning procedure for specific problems including data processing, model building and evaluation
  • Use various Java machine learning libraries and tools

Training Content Outline

  1. Introduction to machine learning
  2. Linear Regression
  3. Logistic regression
  4. Classification
  5. Neural networks
    1. Adalines and Perceptrons
    2. Multi Layer Perceptron and Backpropagatopn
  6. Crossvalidation

Prerequisites

  • Skills: Basic Java  programming
  • Software: Java 8, some Java IDE (preferable NetBeans), Maven, Git

Session at JavaOne 2015

Our JavaOne session ‘Stop the Rot: A Discussion on Maintaining Java SoftwareQuality’ has been accepted!

Abstract
Ever heard about software rot? Technical debt? You can avoid these issues by monitoring software quality to develop sustainable and successful software projects. This panel discussion deals with the essential software quality factors and real-world best practices for maintaining software quality in Java. The panel focuses on how to use open source software quality tools for Java to improve design and coding practices. It also demos using software quality tools such as SonarQube, FindBugs, PMD, and SQE in several open source projects and discusses the results. The attendees will learn about available software quality tools and their features and how to use them to produce better software.
Speakers
Zoran Sevarac, Assistant Professor, Faculty of Organisational Sciences, University of Belgrade
Vladan Devedzic, FON – School of Business Administration, University of Belgrade
Sven Reimers, System Engineer, Airbus Defence and Space
Florian Vogler, System Engineer, Airbus Defence and Space
Martijn Verburg, jClarity