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A guide to understanding the inner workings and outer limits of technology and why we should never assume that computers always get it right.
Machines That Think explores how artificial intelligence helps us understand human intelligence, machines that compose music and write stories - and asks if AI is really a threat.
Using hands-on examples, this practical book shows data scientists and data practitioners how to build their own custom knowledge graphs. Authors Jesus Barrasa and Jim Webber... Læs mere
This practical guide provides a collection of techniques and best practices that are generally overlooked in most data engineering... Læs mere
Machine Learning brings together all the state-of-the-art methods for making sense of data. With hundreds of worked examples and... Læs mere
Machine learning is an interdisciplinary field of science and engineering that studies mathematical theories and practical applications of systems that learn.... Læs mere
This book gives a solid basis for conducting performance evaluations of learning algorithms in practical settings with an emphasis on... Læs mere
In many practical situations it is impossible to run existing machine learning methods on a single computer, because either the data is too... Læs mere
Could a machine have an immaterial mind? The author argues that true conscious machines can be built, but rejects artificial intelligence and classical neural... Læs mere