0

Explore Products

Best Sellers

New Releases

Books

Videos

Audiobooks

Free Learning

Machine Learning in Java

You're reading from Machine Learning in Java Helpful techniques to design, build, and deploy powerful machine learning applications in Java

Product type Paperback

Published in Nov 2018

Publisher Packt

ISBN-13 9781788474399

Length 300 pages

Edition 2nd Edition

Languages

Java

Tools

JAVA-ML

Concepts

Machine Learning

Authors (2):

Ashish Bhatia

Bostjan Kaluza

View More author details

Table of Contents (13) Chapters

Preface

1. Applied Machine Learning Quick Start FREE CHAPTER

2. Java Libraries and Platforms for Machine Learning

3. Basic Algorithms - Classification, Regression, and Clustering

4. Customer Relationship Prediction with Ensembles

5. Affinity Analysis

6. Recommendation Engines with Apache Mahout

7. Fraud and Anomaly Detection

8. Image Recognition with Deeplearning4j

9. Activity Recognition with Mobile Phone Sensors

10. Text Mining with Mallet - Topic Modeling and Spam Detection

11. What Is Next?

12. Other Books You May Enjoy

Leave a review - let other readers know what you think

Image classification

In this section, we will discuss how to implement some of the neural network structures with the Deeplearning4j library. Let's get started.

Deeplearning4j

As we discussed in Chapter 2, Java Libraries and Platforms for Machine Learning, Deeplearning4j is an open source, distributed deep learning project in Java and Scala. Deeplearning4j relies on Spark and Hadoop for MapReduce, trains models in parallel, and iteratively averages the parameters they produce in a central model. A detailed library summary is presented in Chapter 2, Java Libraries and Platforms for Machine Learning.

Getting DL4J

...

The rest of the chapter is locked

Register for a free Packt account to unlock a world of extra content!

A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.

Unlock this book and the full library FREE for 7 days

Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of

Start free trial

Renews at $19.99/month. Cancel anytime

Authors (2)

Ashish Bhatia

Ashish Bhatia

See other products by Ashish Bhatia

Bostjan Kaluza

Bostjan Kaluza

Bostjan Kaluza is a researcher in artificial intelligence and machine learning with extensive experience in Java and Python. Bostjan is the chief data scientist at Evolven, a leading IT operations analytics company. He works with machine learning, predictive analytics, pattern mining, and anomaly detection to turn data into relevant information. Prior to Evolven, Bostjan served as a senior researcher in the department of intelligent systems at the Jozef Stefan Institute and led research projects involving pattern and anomaly detection, ubiquitous computing, and multi-agent systems. In 2013, Bostjan published his first book, Instant Weka How-To, published by Packt Publishing, exploring how to leverage machine learning using Weka.

See other products by Bostjan Kaluza

Other recommended products

Related to this chapter

Java Data Science Cookbook

Java Data Science Cookbook

Java has been one of the most popular languages for developers for several decades and yet the potential of the Java ecosystem still remains untapped when it comes to using JVM-based languages and platforms to solve data science related problems. A variety of tools and libraries are available such as Spark, Hadoop, and Mahout for computation and libraries such as MLlib, Weka, DL4j to implement smart data models. This book uncovers practically all these techniques in the form of recipes showing you how these tools and libraries can solve statistical, analytical, data mining, and information science related problems.

Mar 2017 12h 24m

Hands-On Artificial Intelligence with Java for Beginners

Hands-On Artificial Intelligence with Java for Beginners

This book will introduce the AI algorithms to the beginners and will take on implementing AI tasks using various Java-based libraries. It will take a practical approach to get you up and running with building smarter applications using Java programming knowledge.

Aug 2018 4h 48m

Hands-On Artificial Intelligence with Java for Beginners

Hands-On Artificial Intelligence with Java for Beginners

This book will introduce the AI algorithms to the beginners and will take on implementing AI tasks using various Java-based libraries. It will take a practical approach to get you up and running with building smarter applications using Java programming knowledge.

Aug 2018 4h 48m

Hands-On Artificial Intelligence with Java for Beginners

Hands-On Artificial Intelligence with Java for Beginners

This book will introduce the AI algorithms to the beginners and will take on implementing AI tasks using various Java-based libraries. It will take a practical approach to get you up and running with building smarter applications using Java programming knowledge.

Aug 2018 4h 48m

Java for Data Science

Java for Data Science

Harness the incredible power of Java-based approaches to data science and create new, innovative applications to explore, visualise and analyse big data. With its tutorial approach and step-by-step instructional style, Java for Data Science is the ultimate data science book for Java developers interested in Java-based data science solutions.

Jan 2017 12h 52m

Machine Learning with scikit-learn Quick Start Guide

Machine Learning with scikit-learn Quick Start Guide

Scikit-learn is a robust machine learning library for the Python programming language. It provides a set of supervised and unsupervised learning algorithms. This book is the easiest way to learn how to deploy, optimize and evaluate all the important machine learning algorithms that scikit-learn provides.

Oct 2018 5h 44m

Machine Learning with scikit-learn Quick Start Guide

Machine Learning with scikit-learn Quick Start Guide

Scikit-learn is a robust machine learning library for the Python programming language. It provides a set of supervised and unsupervised learning algorithms. This book is the easiest way to learn how to deploy, optimize and evaluate all the important machine learning algorithms that scikit-learn provides.

Oct 2018 5h 44m

Machine Learning with scikit-learn Quick Start Guide

Machine Learning with scikit-learn Quick Start Guide

Scikit-learn is a robust machine learning library for the Python programming language. It provides a set of supervised and unsupervised learning algorithms. This book is the easiest way to learn how to deploy, optimize and evaluate all the important machine learning algorithms that scikit-learn provides.

Oct 2018 5h 44m

Machine Learning with scikit-learn Quick Start Guide

Machine Learning with scikit-learn Quick Start Guide

Scikit-learn is a robust machine learning library for the Python programming language. It provides a set of supervised and unsupervised learning algorithms. This book is the easiest way to learn how to deploy, optimize and evaluate all the important machine learning algorithms that scikit-learn provides.

Oct 2018 5h 44m

Machine Learning with scikit-learn Quick Start Guide

Machine Learning with scikit-learn Quick Start Guide

Scikit-learn is a robust machine learning library for the Python programming language. It provides a set of supervised and unsupervised learning algorithms. This book is the easiest way to learn how to deploy, optimize and evaluate all the important machine learning algorithms that scikit-learn provides.

Oct 2018 5h 44m

Mastering Java Machine Learning

Mastering Java Machine Learning

Master key Java machine learning libraries and their applications with the help of real-world case studies. Explore advanced machine learning techniques such as anomaly detection, stream learning, active learning, semi-supervised learning, probabilistic graph modeling, text mining, deep learning, and big data batch and stream machine learning.

Jul 2017 18h 32m

Mastering Java Machine Learning

Mastering Java Machine Learning

Master key Java machine learning libraries and their applications with the help of real-world case studies. Explore advanced machine learning techniques such as anomaly detection, stream learning, active learning, semi-supervised learning, probabilistic graph modeling, text mining, deep learning, and big data batch and stream machine learning.

Jul 2017 18h 32m

Personalised recommendations for you

Based on your interests and search pattern

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m