This is a practical "cook book style" book for writing Java 8 applications that features techniques for natural language processing, machine learning, network programming, linked data, and knowledge management.
The examples for this book are open source. Please check out the examples at https://github.com/mark-watson/power-java before buying this book to make sure that the topics are of interest to you. The examples are:
Anomaly detection using the University of Wisconsin cancer data set.
Deep Learning using the deeplearning4j library. I also use the University of Wisconsin cancer data set for this example.
Network programming techniques like directory lookup and UDP multicast that can be useful for game development and Internet of Things applications.
Utilities for dealing with Google Document and Microsoft Office 365 file formats.
Linked Data examples using the DBPedia SPARQL endpoint.
Machine Learning using the Apache Spark mllib library.
Named Entity Recognition example that parses English language text and identifies entities like people and places as Wikipedia/DBPedia unique URIs.
Natural Language Processing (NLP) using the OpenNLP library. In addition to using pre-trained models, I include an example for training a maximum entropy model.
Web scraping example using the JSoup library.
The examples for this book are open source. Please check out the examples at https://github.com/mark-watson/power-java before buying this book to make sure that the topics are of interest to you. The examples are:
Anomaly detection using the University of Wisconsin cancer data set.
Deep Learning using the deeplearning4j library. I also use the University of Wisconsin cancer data set for this example.
Network programming techniques like directory lookup and UDP multicast that can be useful for game development and Internet of Things applications.
Utilities for dealing with Google Document and Microsoft Office 365 file formats.
Linked Data examples using the DBPedia SPARQL endpoint.
Machine Learning using the Apache Spark mllib library.
Named Entity Recognition example that parses English language text and identifies entities like people and places as Wikipedia/DBPedia unique URIs.
Natural Language Processing (NLP) using the OpenNLP library. In addition to using pre-trained models, I include an example for training a maximum entropy model.
Web scraping example using the JSoup library.
