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Machine learning

Showing 1-16 of top 150 Results.

Superintelligence: Paths, Dangers,...
(Paperback)
Nick Bostrom
 
This seminal book injects the topic of superintelligence into the academic and popular mainstream. What happens when machines surpass humans in general intelligence? Will artificial agents save or destroy us?...
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Superintelligence: Paths, Dangers,...
(Hardback)
Nick Bostrom
 
This seminal book injects the topic of superintelligence into the academic and popular mainstream. What happens when machines surpass humans in general intelligence? Will artificial agents save or destroy us?...
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£18.99
 
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Machine Learning: A Probabilistic...
(Hardback)
Kevin P. Murphy
 
Today's Web-enabled deluge of electronic data calls for automated methods of data analysis. Machine learning provides these, developing methods that can automatically...
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Pattern Recognition and Machine Learning
(Hardback)
Christopher M. Bishop
This is the first textbook on pattern recognition to present the Bayesian viewpoint. It presents approximate inference algorithms that permit fast approximate answers in situations where exact answers are not...
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The Technological Singularity
(Paperback)
Murray Shanahan
 
The idea that human history is approaching a "singularity" -- that ordinary humans will someday be overtaken by artificially intelligent machines or cognitively...
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Thoughtful Machine Learning: A...
(Paperback)
Matthew Kirk
 
In this practical guide, author Matthew Kirk takes you through the principles of TDD and machine learning, and shows you how to apply TDD to several machine-learning algorithms, including Naive...
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Probabilistic Graphical Models:...
(Hardback)
Daphne Koller; Nir Friedman
A general framework for constructing and using probabilistic models of complex systems that would enable a computer to use available information for making decisions.
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Machine Learning: An Algorithmic...
(Books & other media combined)
Stephen Marsland
 
A Proven, Hands-On Approach for Students without a Strong Statistical Foundation Since the best-selling first edition was published, there have been several prominent...
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Fundamentals of Machine Learning for...
(Hardback)
John D. Kelleher; Brian Mac Namee;...
 
Machine learning is often used to build predictive models by extracting patterns from large datasets. These models are used in predictive data analytics applications...
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Building Machine Learning Systems ...
(Paperback)
Willi Richert; Luis Pedro Coelho;...
 
This is a tutorial-driven and practical, but well-grounded book showcasing good Machine Learning practices. There will be an emphasis on using existing technologies...
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Machine Learning: Hands-On for...
(Paperback)
Jason Bell
 
Dig deep into the data with a hands-on guide to machine learning Machine Learning: Hands-On for Developers and Technical Professionals provides hands-on instruction and fully-coded working examples...
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£33.99
 
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Machine Learning in Python: Essential...
(Paperback)
Michael Bowles
 
Learn a simpler and more effective way to analyze data and predict outcomes with Python Machine Learning in Python shows you how to successfully analyze data using...
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Building a Recommendation Engine with...
(Paperback)
Saleem A. Ansari
 
Learn to use Scala to build a recommendation engine from scratch and empower your website users About This Book * Learn the basics of a recommendation engine and...
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The Intelligent Web: Search, Smart...
(Hardback)
Gautam Shroff
 
Early hopes for Artificial Intelligence soon evaporated. But, driven by the need for smarter searching and advert placing, increasingly sophisticated algorithms, combined with the sheer amount of data on the...
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The Elements of Statistical Learning:...
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Trevor Hastie; Robert Tibshirani;...
 
This major new edition features many topics not covered in the original, including graphical models, random forests, and ensemble methods. As before, it covers the conceptual framework for statistical data...
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Machine Learning for Hackers
(Paperback)
Drew Conway; John Myles White
 
Now that storage and collection technologies are cheaper and more precise, methods for extracting relevant information from large datasets is within the reach any experienced programmer willing to crunch data.
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