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Intelligent Systems and Financial Forecasting / Jason Kingdon

£29.99

Product description

Slight creasing near the spine from the book having been read - otherwise there is very little wear on the cover. Internally, the book is clean, tight and unmarked.

A fundamental objective of Artificial Intelligence (AI) is the creation of intelligent computer programs. In more modest terms AI is simply concerned with expanding the repertoire of computer applications into new domains and to new levels of efficiency. The motivation for this effort comes from many sources. At a practical level there is always a demand for achieving things in more efficient ways. Equally, there is the technical challenge of building programs that allow a machine to do something a machine has never done before. Both of these desires are contained within AI and both provide the inspirational force behind its development. In terms of satisfying both of these desires there can be no better example than machine learning. Machines that can learn have an in-built efficiency. The same software can be applied in many applications and in many circumstances. The machine can adapt its behaviour so as to meet the demands of new, or changing, environments without the need for costly re-programming. In addition, a machine that can learn can be applied in new domains with the genuine potential for innovation. In this sense a machine that can learn can be applied in areas where little is known about possible causal relationships, and even in circumstances where causal relationships are judged not to exist. This last aspect is of major significance when considering machine learning as applied to financial forecasting.

Item details

Author(s):
Jason Kingdon
Condition:
Used: very good
Dimensions:
15.5 x 23.5 x 1.5 cm
Edition:
1st
Format:
Paperback
ISBN-10:
3540760989
ISBN-13:
9783540760986
Number of pages:
227
Publisher:
Springer (1997)
Title:
Intelligent Systems and Financial Forecasting

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About this item

Slight creasing near the spine from the book having been read - otherwise there is very little wear on the cover. Internally, the book is clean, tight and unmarked.

A fundamental objective of Artificial Intelligence (AI) is the creation of intelligent computer programs. In more modest terms AI is simply concerned with expanding the repertoire of computer applications into new domains and to new levels of efficiency. The motivation for this effort comes from many sources. At a practical level there is always a demand for achieving things in more efficient ways. Equally, there is the technical challenge of building programs that allow a machine to do something a machine has never done before. Both of these desires are contained within AI and both provide the inspirational force behind its development. In terms of satisfying both of these desires there can be no better example than machine learning. Machines that can learn have an in-built efficiency. The same software can be applied in many applications and in many circumstances. The machine can adapt its behaviour so as to meet the demands of new, or changing, environments without the need for costly re-programming. In addition, a machine that can learn can be applied in new domains with the genuine potential for innovation. In this sense a machine that can learn can be applied in areas where little is known about possible causal relationships, and even in circumstances where causal relationships are judged not to exist. This last aspect is of major significance when considering machine learning as applied to financial forecasting.

Author(s):
Jason Kingdon
Condition:
Used: very good
Dimensions:
15.5 x 23.5 x 1.5 cm
Edition:
1st
Format:
Paperback
ISBN-10:
3540760989
ISBN-13:
9783540760986
Number of pages:
227
Publisher:
Springer (1997)
Title:
Intelligent Systems and Financial Forecasting

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