To get the most out of this book

This book will teach you how to build advanced machine learning applications with intuitive and detailed explanations of topics, and with no background in math required. It adopts a practical approach by applying the theory to build real-world Java applications using modern practices and techniques that are prevalent in the computer vision world.

Download the example code files

You can download the example code files for this book from your account at www.packt.com. If you purchased this book elsewhere, you can visit www.packt.com/support and register to have the files emailed directly to you.

You can download the code files by following these steps:

1. Log in or register at www.packt.com.
2. Select the SUPPORT tab.
3. Click on Code Downloads & Errata.
4. Enter the name of the book in the Search box and follow the onscreen instructions.

Once the file is downloaded, please make sure that you unzip or extract the folder using the latest version of:

• WinRAR/7-Zip for Windows
• Zipeg/iZip/UnRarX for Mac
• 7-Zip/PeaZip for Linux

The code bundle for the book is also hosted on GitHub at https://github.com/PacktPublishing/Hands-On-Java-Machine-Learning-for-Computer-Vision. In case there's an update to the code, it will be updated on the existing GitHub repository.

We also have other code bundles from our rich catalog of books and videos available at https://github.com/PacktPublishing/. Check them out!

Download the color images

We also provide a PDF file that has color images of the screenshots/diagrams used in this book. You can download it here: https://www.packtpub.com/sites/default/files/downloads/9781789613964_ColorImages.pdf.

Conventions used

There are a number of text conventions used throughout this book.

CodeInText: Indicates code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles. Here is an example: "Now, detectEdges is exposed to the graphical user interface, to detect edges, and it takes two inputs: the colored image, bufferedImage, and the filter selected by the user, selectedFilter."

A block of code is set as follows:

package ramo.klevis.ml;
import javax.imageio.ImageIO;
import java.awt.*;
import java.awt.image.BufferedImage;
import java.io.File;
import java.io.IOException;
import java.util.HashMap;
public class EdgeDetection {

Bold: Indicates a new term, an important word, or words that you see on screen. For example, words in menus or dialog boxes appear in the text like this. Here is an example: "So if we take the block highlighted in the screenshot, we'll multiply 1 by 255, add 0 multiplied by 255, and then subtract 1 multiplied by 255."

Warnings or important notes appear like this.

Tips and tricks appear like this.