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Fun Functional Introduction Machine by Psaris Nick (12 results)
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Condition: New.
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Fun Q: A Functional Introduction to Machine Learning in Q (Paperback or Softback)
Language: English
Published by Vector SIGMA 7/16/2020, 2020
ISBN 10: 1734467509 ISBN 13: 9781734467505
Paperback or Softback. Condition: New. Fun Q: A Functional Introduction to Machine Learning in Q. Book.
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Condition: As New. Unread book in perfect condition.
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Fun Q: A Functional Introduction to Machine Learning in Q
Language: English
Published by Vector Sigma 2020-07, 2020
ISBN 10: 1734467509 ISBN 13: 9781734467505
PF. Condition: New.
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Fun Q: A Functional Introduction to Machine Learning in Q
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: New.
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Fun Q: A Functional Introduction to Machine Learning in Q
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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Fun Q: A Functional Introduction to Machine Learning in Q
Seller: THE SAINT BOOKSTORE, Southport, United Kingdom
Seller rating 5 out of 5 stars
£ 49.47
£ 12.97 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.
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Condition: New. Print on Demand pp. 415.
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Condition: New. Print on Demand pp. 415.
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Condition: New. PRINT ON DEMAND pp. 415.
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Taschenbuch. Condition: Neu. Fun Q | A Functional Introduction to Machine Learning in Q | Nick Psaris | Taschenbuch | Kartoniert / Broschiert | Englisch | 2020 | Vector Sigma | EAN 9781734467505 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Bring the power of machine learning to the fastest time-series database. Fun Q uses the powerful q programming language to implement many of the most famous machine-learning algorithms. Using a meticulously factored machine-learning library, each algorithm is broken into its basic building blocks and then rebuilt from scratch. Famous machine-learning data sets are used to motivate each chapter as advanced q idioms are introduced. Whether you are a data scientist who is new to q or a kdb+ administrator who is new to machine learning, you'll have fun learning how machine-learning algorithms can be implemented in the concise vector-functional language q. With nothing but the q binary, you'll be able to download data sets, generate plots in the q terminal and get progress-bar-style feedback as model parameters iteratively improve. In addition to being a functional introduction to machine learning algorithms in q, it is designed to be a fun introduction as well!
