Book Details:
Pages: | 386 |
Published: | Jul 15 2013 |
Posted: | Nov 19 2014 |
Language: | English |
Book format: | PDF |
Book size: | 4.3 MB |
Book Description:
Gain hands-on experience with SPARQL, the RDF query language that's bringing new possibilities to semantic web, linked data, and big data projects. This updated and expanded edition shows you how to use SPARQL 1.1 with a variety of tools to retrieve, manipulate, and federate data from the public web as well as from private sources. Author Bob DuCharme has you writing simple queries right away before providing background on how SPARQL fits into RDF technologies. Using short examples that you can run yourself with open source software, you'll learn how to update, add to, and delete data in RDF datasets.Get the big picture on RDF, linked data, and the semantic web Use SPARQL to find bad data and create new data from existing data Use datatype metadata and functions in your queries Learn techniques and tools to help your queries run more efficiently Use RDF Schemas and OWL ontologies to extend the power of your queries Discover the roles that SPARQL can play in your applications
A complete guide to successful learning using Moodle
A complete guide to successful learning using Moodle, focused on course development and delivery and using the best educational practices. Moodle is relatively easy to install and use, but the real challenge is to develop a learning process that leverages its power and maps effectively onto the content established learning situation. This book guides you through meeting that challenge. This book is for anyone who wants to get the best from Moodle. Beginners will get a thorough guide to how the software works, with great ideas for getting off to a good start with their first course. More experienced Moodlers will find powerful insights into developing more successful and educational courses....
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Machine Learning in Python
Incorporating machine learning in your applications is becoming essential. As a programmer this book is the ideal introduction to scikit-learn for your Python environment, taking your skills to a whole new level. Overview Use Python and scikit-learn to create intelligent applications Apply regression techniques to predict future behaviour and learn to cluster items in groups by their similarities Make use of classification techniques to perform image recognition and document classification In Detail Machine learning, the art of creating applications that learn from experience and data, has been around for many years. However, in the era of big data, huge amounts of information is being generated. This makes machine learning an unavoidable source o...
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