San Francisco Public Library

Hands-on artificial intelligence with Java for beginners, build intelligent apps using machine learning and deep learning with Deeplearning4j, Nisheeth Joshi

eng

illustrations

no index present

non fiction

Hands-on artificial intelligence with Java for beginners

dictionaries

1055555822

Nisheeth Joshi

build intelligent apps using machine learning and deep learning with Deeplearning4j

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

Cover; Title Page; Copyright and Credits; Packt Upsell; Contributors; Table of Contents; Preface; Chapter 1: Introduction to Artificial Intelligence and Java; What is machine learning?; Differences between classification and regression; Installing JDK and JRE; Setting up the NetBeans IDE; Importing Java libraries and exporting code in projects as a JAR file; Summary; Chapter 2: Exploring Search Algorithms; An introduction to searching; Implementing Dijkstra's search; Understanding the notion of heuristics; A brief introduction to the A* algorithm; Implementing an A* algorithm; SummaryChapter 3: AI Games and the Rule-Based SystemIntroducing the min-max algorithm; Implementing an example min-max algorithm; Installing Prolog; An introduction to rule-based systems with Prolog; Setting up Prolog with Java; Executing Prolog queries using Java; Summary; Chapter 4: Interfacing with Weka; An introduction to Weka; Installing and interfacing with Weka; Calling the Weka environment into Java; Reading and writing datasets; Converting datasets; Converting an ARFF file to a CSV file; Converting a CSV file to an ARFF file; Summary; Chapter 5: Handling Attributes; Filtering attributesDiscretizing attributesAttribute selection; Summary; Chapter 6: Supervised Learning; Developing a classifier; Model evaluation; Making predictions; Loading and saving models; Summary; Chapter 7: Semi-Supervised and Unsupervised Learning; Working with k-means clustering; Evaluating a clustering model; An introduction to semi-supervised learning; The difference between unsupervised and semi-supervised learning; Self-training and co-training machine learning models; Downloading a semi-supervised package; Creating a classifier for semi-supervised modelsMaking predictions with semi-supervised machine learning modelsSummary; Other Books You May Enjoy; Index