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Books > Computing & IT > Applications of computing > Artificial intelligence
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Learning to Learn (Paperback, Softcover reprint of the original 1st ed. 1998)
Loot Price: R5,842
Discovery Miles 58 420
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Learning to Learn (Paperback, Softcover reprint of the original 1st ed. 1998)
Expected to ship within 18 - 22 working days
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Over the past three decades or so, research on machine learning and
data mining has led to a wide variety of algorithms that learn
general functions from experience. As machine learning is maturing,
it has begun to make the successful transition from academic
research to various practical applications. Generic techniques such
as decision trees and artificial neural networks, for example, are
now being used in various commercial and industrial applications.
Learning to Learn is an exciting new research direction within
machine learning. Similar to traditional machine-learning
algorithms, the methods described in Learning to Learn induce
general functions from experience. However, the book investigates
algorithms that can change the way they generalize, i.e., practice
the task of learning itself, and improve on it. To illustrate the
utility of learning to learn, it is worthwhile comparing machine
learning with human learning. Humans encounter a continual stream
of learning tasks. They do not just learn concepts or motor skills,
they also learn bias, i.e., they learn how to generalize. As a
result, humans are often able to generalize correctly from
extremely few examples - often just a single example suffices to
teach us a new thing. A deeper understanding of computer programs
that improve their ability to learn can have a large practical
impact on the field of machine learning and beyond. In recent
years, the field has made significant progress towards a theory of
learning to learn along with practical new algorithms, some of
which led to impressive results in real-world applications.
Learning to Learn provides a survey of some of the most exciting
new research approaches, written by leading researchers in the
field. Its objective is to investigate the utility and feasibility
of computer programs that can learn how to learn, both from a
practical and a theoretical point of view.
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