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Could you provide a link to a sample chapter and table of contents? Thanks!

mark_l_watson 13y ago
I am putting together a sample with the first and last chapter, but it may not be on the book page until tomorrow morning.
lpolovets 13y ago
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
- mark_l_watson 13y ago
  Thanks for posting that! And, of course, thanks for buying a copy of my book.
  - FraaJad 13y ago
    Could you please paste this under "Table of Contents" of the book page? That would help people decide.
- wiradikusuma 13y ago
  This is stupid question, but based on the ToC, is this book suitable for Java programmer who doesn't know anything about AI other than from Hollywood movies?
  - eli_gottlieb 13y ago
    Almost definitely not, from the look of it. Even the first few chapters go beyond my old CS387 Intro to AI class in college. I feel like now that I'm in grad school I should take more and better AI courses, but I just can't find the interest in me, no matter that the field is economically hot right now.
- zura 13y ago
  This looks like a pretty broad coverage book. I wonder if the book has same issues as other broad books - they do good in telling you what topics exist but fail to go in depth.
  - mark_l_watson 13y ago
    Hello Zura, that is a fair comment. I don't go into a lot of depth for some topics. I introduce an idea, usually explore an idea with some code, and try to suggest possible projects. If you want a thorough and deep coverage of AI, work through http://aima.cs.berkeley.edu/ http://aima.cs.berkeley.edu/

I am putting together a sample with the first and last chapter, but it may not be on the book page until tomorrow morning.

lpolovets 13y ago

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

mark_l_watson 13y ago
Thanks for posting that! And, of course, thanks for buying a copy of my book.
- FraaJad 13y ago
  Could you please paste this under "Table of Contents" of the book page? That would help people decide.
wiradikusuma 13y ago
This is stupid question, but based on the ToC, is this book suitable for Java programmer who doesn't know anything about AI other than from Hollywood movies?
- eli_gottlieb 13y ago
  Almost definitely not, from the look of it. Even the first few chapters go beyond my old CS387 Intro to AI class in college. I feel like now that I'm in grad school I should take more and better AI courses, but I just can't find the interest in me, no matter that the field is economically hot right now.
zura 13y ago
This looks like a pretty broad coverage book. I wonder if the book has same issues as other broad books - they do good in telling you what topics exist but fail to go in depth.
- mark_l_watson 13y ago
  Hello Zura, that is a fair comment. I don't go into a lot of depth for some topics. I introduce an idea, usually explore an idea with some code, and try to suggest possible projects. If you want a thorough and deep coverage of AI, work through http://aima.cs.berkeley.edu/ http://aima.cs.berkeley.edu/