By Mark Watson

It is a sensible "cook booklet type" e-book for writing Java eight functions that includes innovations for ordinary language processing, desktop studying, community programming, associated info, and information administration.

The examples for this booklet are open resource. Please try out the examples at prior to procuring this ebook to ensure that the subjects are of curiosity to you. The examples are:

Anomaly detection utilizing the college of Wisconsin melanoma info set.

Deep studying utilizing the deeplearning4j library. I additionally use the collage of Wisconsin melanoma info set for this example.

Network programming suggestions like listing look up and UDP multicast that may be helpful for online game improvement and web of items applications.

Utilities for facing Google rfile and Microsoft place of work 365 dossier formats.

Linked info examples utilizing the DBPedia SPARQL endpoint.

Machine studying utilizing the Apache Spark mllib library.

Named Entity acceptance instance that parses English language textual content and identifies entities like humans and locations as Wikipedia/DBPedia targeted URIs.

Natural Language Processing (NLP) utilizing the OpenNLP library. as well as utilizing pre-trained versions, I comprise an instance for education a greatest entropy model.

Web scraping instance utilizing the JSoup library.

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We will train one model to recognize the categories of COMPUTERS, ECONOMY, HEALTH, and POLITICS. You should then have the knowledge for training your own models using your own training texts for the categories that you need for your applications. We will also use both some pre-trained models that are included with the OpenNLP distribution and the classification mode that we will soon create in the next chapter when we learn how to perform scalable machine learning algorithms using the Apache Spark platform where we look at techniques for processing very large collections of text to discover information.

Indicates that we are searching the local network (for example, your home network created by a router from your local ISP). local. local. APPLICATION getNiceTextString: any data for FOO123 Do you want to find all local services? Then you can also create a listener that will notify you of all local HTTP services. java written by Werner Randelshofer. iot and added it to the git repository for this book. DiscoverServices While it is often useful to find all local services, I expect that for your own projects you will be writing both service and client applications that cooperate on your local network.

Currently, OpenNLP has support for Danish, German, English, Spanish, Portuguese, and Swedish. I include in the github repository some trained models for English that are used in the examples in this chapter. 5 models). I use OpenNLP for some of the NLP projects that I do for my consulting customers. com that is a commercial product. For customers who can use the GPL license I sometimes use the Stanford NLP libraries that, like OpenNLP, are written in Java. The following figure shows the project for this chapter in the Community Edition of IntelliJ: IntelliJ project view for the examples in this chapter We will use pre-trained models for tokenizing text, recognizing the names of organizations, people, locations, and parts of speech for words in input text.

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