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Hands-on artificial intelligence with Java for beginners : 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.

Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Joshi, Nisheeth (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Birmingham, UK : Packt Publishing, 2018.
Temas:
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)

MARC

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100 1 |a Joshi, Nisheeth,  |e author. 
245 1 0 |a Hands-on artificial intelligence with Java for beginners :  |b build intelligent apps using machine learning and deep learning with Deeplearning4j /  |c Nisheeth Joshi. 
264 1 |a Birmingham, UK :  |b Packt Publishing,  |c 2018. 
300 |a 1 online resource :  |b illustrations 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
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588 0 |a Online resource; title from title page (Safari, viewed October 2, 2018). 
505 0 |a 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; Summary 
505 8 |a Chapter 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 attributes 
505 8 |a Discretizing 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 models 
505 8 |a Making predictions with semi-supervised machine learning modelsSummary; Other Books You May Enjoy; Index 
520 |a 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. 
590 |a O'Reilly  |b O'Reilly Online Learning: Academic/Public Library Edition 
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650 0 |a Problem solving  |x Computer programs. 
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650 6 |a Apprentissage automatique. 
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650 7 |a Machine learning.  |2 fast  |0 (OCoLC)fst01004795 
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