I just bought the book (at $6, it is an easy impulse buy...) Table of contents: Introduction # Other JVM Languages # Github Repository for Book Softwa

I just bought the book (at $6, it is an easy impulse buy...) Table of contents: Introduction # Other JVM Languages # Github Repository for Book Software # Use of Java Generics and Native Types # Notes on Java Coding Styles Used in this Book # Book Summary Search # Representation of Search State Space and Search Operators # Finding Paths in Mazes # Finding Paths in Graphs # Adding Heuristics to Breadth First Search # Search and Game Playing Reasoning # Logic # PowerLoom Overview # Running PowerLoom Interactively # Using the PowerLoom APIs in Java Programs # Suggestions for Further Study Semantic Web # Relational Database Model Has Problems Dealing with Rapidly Changing Data Requirements 59 # RDF: The Universal Data Format # Extending RDF with RDF Schema # The SPARQL Query Language # Using Sesame # OWL: The Web Ontology Language # Knowledge Representation and REST # Material for Further Study Expert Systems # Production Systems # The Drools Rules Language # Using Drools in Java Applications # Example Drools Expert System: Blocks World # Example Drools Expert System: Help Desk System # Notes on the Craft of Building Expert Systems Genetic Algorithms # Theory # Java Library for Genetic Algorithms # Finding the Maximum Value of a Function Machine Learning with Weka # Using Weka’s Interactive GUI Application # Interactive Command Line Use of Weka # Embedding Weka in a Java Application # Suggestions for Further Study Neural Networks # Hopfield Neural Networks # Java Classes for Hopfield Neural Networks # Testing the Hopfield Neural Network Class # Back Propagation Neural Networks # A Java Class Library for Back Propagation # Adding Momentum to Speed Up Back-Prop Training Statistical Natural Language Processing # Tokenizing, Stemming, and Part of Speech Tagging Text # Named Entity Extraction From Text # Using the WordNet Linguistic Database # Automatically Assigning Tags to Text # Text Clustering # Spelling Correction # Hidden Markov Models Information Gathering # Open Calais # Information Discovery in Relational Databases # Down to the Bare Metal: In-Memory Index and Search # Indexing and Search Using Embedded Lucene # Indexing and Search with Nutch Clients Data Science Techniques # A Mix of Open Source and Proprietary Tools # Handling “small big data” in a Cost Effective Way # Writing and Testing MapReduce Applications # Example Application: MapReduce Application for Finding Proper Names in Text # Using Inexpensive Large Memory Leased Servers # Example Application Idea: Using the Google Book Project NGRAM Data Sets # Example Application Idea: Using Wikipedia Data Dumps # Conclusion Conclusions