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Practical Machine Learning New by Dunning Ted (24 results)
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Paperback. Condition: Very Good. No Jacket. May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less.
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Condition: As New. Unread book in perfect condition.
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Condition: New.
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Practical Machine Learning - A New Look at Anomaly Detection
Seller: Rarewaves.com USA, London, LONDO, United Kingdom
Seller rating 5 out of 5 stars
Paperback. Condition: New. Anomaly detection is the detective work of machine learning: finding the unusual, catching the fraud, discovering strange activity in large and complex datasets. But, unlike Sherlock Holmes, you may not know what the puzzle is, much less what "suspects" you're looking for. This O'Reilly report uses practical examples to explain how the underlying concepts of anomaly detection work. From banking security to natural sciences, medicine, and marketing, anomaly detection has many useful applications in this age of big data. And the search for anomalies will intensify once the Internet of Things spawns even more new types of data. The concepts described in this report will help you tackle anomaly detection in your own project.Use probabilistic models to predict what's normal and contrast that to what you observe Set an adaptive threshold to determine which data falls outside of the normal range, using the t-digest algorithm Establish normal fluctuations in complex systems and signals (such as an EKG) with a more adaptive probablistic model Use historical data to discover anomalies in sporadic event streams, such as web traffic Learn how to use deviations in expected behavior to trigger fraud alerts.
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Paperback. Condition: New. Anomaly detection is the detective work of machine learning: finding the unusual, catching the fraud, discovering strange activity in large and complex datasets. But, unlike Sherlock Holmes, you may not know what the puzzle is, much less what "suspects" you're looking for. This O'Reilly report uses practical examples to explain how the underlying concepts of anomaly detection work. From banking security to natural sciences, medicine, and marketing, anomaly detection has many useful applications in this age of big data. And the search for anomalies will intensify once the Internet of Things spawns even more new types of data. The concepts described in this report will help you tackle anomaly detection in your own project.Use probabilistic models to predict what's normal and contrast that to what you observe Set an adaptive threshold to determine which data falls outside of the normal range, using the t-digest algorithm Establish normal fluctuations in complex systems and signals (such as an EKG) with a more adaptive probablistic model Use historical data to discover anomalies in sporadic event streams, such as web traffic Learn how to use deviations in expected behavior to trigger fraud alerts.
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PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.
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Practical Machine Learning: A New Look at Anomaly Detection (Paperback or Softback)
Language: English
Published by O'Reilly Media 9/6/2014, 2014
ISBN 10: 1491911603 ISBN 13: 9781491911600
Paperback or Softback. Condition: New. Practical Machine Learning: A New Look at Anomaly Detection. Book.
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Condition: New.
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Condition: New. pp. 66.
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Practical Machine Learning - A New Look at Anomaly Detection
Language: English
Published by O'Reilly Media, Inc, USA, 2014
ISBN 10: 1491911603 ISBN 13: 9781491911600
Seller: THE SAINT BOOKSTORE, Southport, United Kingdom
Seller rating 5 out of 5 stars
Paperback / softback. Condition: New. New copy - Usually dispatched within 4 working days.
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Practical Machine Learning : A New Look at Anomaly Detection
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: New.
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Condition: New. pp. 66.
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Practical Machine Learning : A New Look at Anomaly Detection
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: As New. Unread book in perfect condition.
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Practical Machine Learning - A New Look at Anomaly Detection
Seller: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Ireland
Seller rating 5 out of 5 stars
First Edition
Condition: New. This O'Reilly report uses practical example to explain how the underlying concepts of anomaly detection work. Num Pages: 66 pages, colour illustrations. BIC Classification: UY. Category: (XV) Technical / Manuals. Dimension: 152 x 220 x 4. Weight in Grams: 112. . 2014. 1st Edition. Paperback. . . . .
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paperback. Condition: Used; Very Good. Dispatched, from the UK, within 48 hours of ordering. Though second-hand, the book is still in very good shape. Minimal signs of usage may include very minor creasing on the cover or on the spine.
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Paperback. Condition: Brand New. 66 pages. 9.00x6.00x0.25 inches. In Stock.
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Condition: New. This O'Reilly report uses practical example to explain how the underlying concepts of anomaly detection work. Num Pages: 66 pages, colour illustrations. BIC Classification: UY. Category: (XV) Technical / Manuals. Dimension: 152 x 220 x 4. Weight in Grams: 112. . 2014. 1st Edition. Paperback. . . . . Books ship from the US and Ireland.
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Paperback. Condition: New. Anomaly detection is the detective work of machine learning: finding the unusual, catching the fraud, discovering strange activity in large and complex datasets. But, unlike Sherlock Holmes, you may not know what the puzzle is, much less what "suspects" you're looking for. This O'Reilly report uses practical examples to explain how the underlying concepts of anomaly detection work. From banking security to natural sciences, medicine, and marketing, anomaly detection has many useful applications in this age of big data. And the search for anomalies will intensify once the Internet of Things spawns even more new types of data. The concepts described in this report will help you tackle anomaly detection in your own project.Use probabilistic models to predict what's normal and contrast that to what you observe Set an adaptive threshold to determine which data falls outside of the normal range, using the t-digest algorithm Establish normal fluctuations in complex systems and signals (such as an EKG) with a more adaptive probablistic model Use historical data to discover anomalies in sporadic event streams, such as web traffic Learn how to use deviations in expected behavior to trigger fraud alerts.
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Condition: New. This O Reilly report uses practical example to explain how the underlying concepts of anomaly detection work.Finding Data Anomalies You Didn t Know to Look FornAnomaly detection is the detective work of machine learning: finding the unusual, catching th.
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Practical Machine Learning: A New Look at Anomaly Detection
Language: English
Published by O'reilly Media Sep 2014, 2014
ISBN 10: 1491911603 ISBN 13: 9781491911600
Taschenbuch. Condition: Neu. Neuware - Finding Data Anomalies You Didn't Know to Look ForAnomaly detection is the detective work of machine learning: finding the unusual, catching the fraud, discovering strange activity in large and complex datasets. But, unlike Sherlock Holmes, you may not know what the puzzle is, much less what 'suspects' you're looking for. This O'Reilly report uses practical examples to explain how the underlying concepts of anomaly detection work.From banking security to natural sciences, medicine, and marketing, anomaly detection has many useful applications in this age of big data. And the search for anomalies will intensify once the Internet of Things spawns even more new types of data. The concepts described in this report will help you tackle anomaly detection in your own project. Use probabilistic models to predict what's normal and contrast that to what you observe Set an adaptive threshold to determine which data falls outside of the normal range, using the t-digest algorithm Establish normal fluctuations in complex systems and signals (such as an EKG) with a more adaptive probablistic model Use historical data to discover anomalies in sporadic event streams, such as web traffic Learn how to use deviations in expected behavior to trigger fraud alerts.
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Paperback. Condition: New. Anomaly detection is the detective work of machine learning: finding the unusual, catching the fraud, discovering strange activity in large and complex datasets. But, unlike Sherlock Holmes, you may not know what the puzzle is, much less what "suspects" you're looking for. This O'Reilly report uses practical examples to explain how the underlying concepts of anomaly detection work. From banking security to natural sciences, medicine, and marketing, anomaly detection has many useful applications in this age of big data. And the search for anomalies will intensify once the Internet of Things spawns even more new types of data. The concepts described in this report will help you tackle anomaly detection in your own project.Use probabilistic models to predict what's normal and contrast that to what you observe Set an adaptive threshold to determine which data falls outside of the normal range, using the t-digest algorithm Establish normal fluctuations in complex systems and signals (such as an EKG) with a more adaptive probablistic model Use historical data to discover anomalies in sporadic event streams, such as web traffic Learn how to use deviations in expected behavior to trigger fraud alerts.
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Paperback. Condition: Brand New. 66 pages. 9.00x6.00x0.25 inches. In Stock. This item is printed on demand.
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Practical Machine Learning - A New Look at Anomaly Detection
Language: English
Published by O'Reilly Media, Inc, USA, 2014
ISBN 10: 1491911603 ISBN 13: 9781491911600
Seller: THE SAINT BOOKSTORE, Southport, United Kingdom
Seller rating 5 out of 5 stars
£ 20.97
£ 15.75 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketPaperback / softback. Condition: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.
