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This Machine Learning for Java Developers Training course is a hands-on introduction to core Machine Learning techniques, this course will familiarise you with the Machine Learning landscape as well as providing practical experience.

Learning Objectives

  •     To have a familiarity with the Machine Learning landscape
  •     Understand the different types of Machine Learning algorithms
  •     Identify suitable Machine Learning techniques for different types of data
  •     To be able to implement and evaluate basic Machine Learning algorithms in Java

Machine Learning for Java Developers Training

Course Code

GTMLJ1

Duration

2 Days Practical

Accreditation

N/A

Target Audience

This is ideally suited for Java developers with over 2 years experience. No Machine Learning experience is required.

Attendee Requirements

Proficiency in Java development

Course set-up

  •     Laptop with Java 8
  •     A suitable IDE (Eclipse, Netbeans, IntelliJ)
  •     Maven

 

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Course Description

This Machine Learning for Java Developers Training course is a hands-on introduction to core Machine Learning techniques, this course will familiarise you with the Machine Learning landscape as well as providing practical experience.

Learning Objectives

  •     To have a familiarity with the Machine Learning landscape
  •     Understand the different types of Machine Learning algorithms
  •     Identify suitable Machine Learning techniques for different types of data
  •     To be able to implement and evaluate basic Machine Learning algorithms in Java
Course Outline

Day 1: The Machine Learning Landscape

Introduction

  •     A high level overview of key Machine Learning concepts
  •     Overview of Machine Learning tools and resources for Java

Topic 1

  •     Introduction to Regression: a supervised learning technique
  •     Regression analysis
  •     Regression lab

Topic 2

  •     Working with data
  •     Feature transformation introduction and demonstration
  •     Feature selection introduction and demonstration
  •     Feature selection and transformation labs

Topic 3

  •     Introduction to clustering: an unsupervised learning technique
  •     Clustering lab

Topic 4

  •     Introduction to data classification
  •     Classifying data using Naïve Bayes demonstration

Topic 5

  •     Introduction to learning with ensembles
  •     Ensembles lab

Day 2: Neural Networks

Introduction

  •     Introduction to Neural Networks
  •     Introduction to DeepLearning4J
  •     Demonstration

Topic 1

  •     A simple network: lab
  •     Tuning and hyperparameters

Topic 2

    More complex network labs:

  •         Image recognition
  •         Recurrent Neural Networks
Ways to Attend
  • Attend a public course, check our schedule
  • Private onsite Team training also available

Private Team Training is available for this course

We deliver this course either on or off-site in various regions around the world, and can customise your delivery to suit your exact business needs. Talk to us about how we can fine-tune a course to suit your team's current skillset and ultimate learning objectives.

Private Team Training | Contact us

Technical ICT learning & mentoring services

Private Team Training

Our instructors are specialist consultants with vast real world experience and expertise allowing them to design and deliver client-focused courses for your organisation.

Learn more about our Private Team Training

What Our Clients Say

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About GuruTeam

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