Deep Learning Basics Python by Saitoh Koki (8 results)
- Softcover
Seller: Lucky's Textbooks, Dallas, TX, U.S.A.Lucky's Textbooks
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- Softcover
Seller: BargainBookStores, Grand Rapids, MI, U.S.A.BargainBookStores
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Paperback or Softback. Condition: New. Deep Learning from the Basics: Python and Deep Learning: Theory and Implementation. Book.
- Softcover
Seller: California Books, Miami, FL, U.S.A.California Books
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- Softcover
Seller: Ria Christie Collections, Uxbridge, United KingdomRia Christie Collections
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- Softcover
Seller: Chiron Media, Wallingford, United KingdomChiron Media
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- Softcover
- Print on Demand
Seller: THE SAINT BOOKSTORE, Southport, United KingdomTHE SAINT BOOKSTORE
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Paperback / softback. Condition: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.
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- Print on Demand
Seller: preigu, Osnabrück, Germanypreigu
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Taschenbuch. Condition: Neu. Deep Learning from the Basics | Python and Deep Learning: Theory and Implementation | Koki Saitoh | Taschenbuch | Kartoniert / Broschiert | Englisch | 2021 | Packt Publishing | EAN 9781800206137 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de |… Anbieter: preigu Print on Demand.
- Softcover
- Print on Demand
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Deep learning is rapidly becoming the most preferred way of solving data problems. This is thanks, in part, to its huge variety of mathematical algorithms and their ability to find patterns that are otherwise invisible to us.Deep Learnin…g from the Basics begins with a fast-paced introduction to deep learning with Python, its definition, characteristics, and applications. You'll learn how to use the Python interpreter and the script files in your applications, and utilize NumPy and Matplotlib in your deep learning models. As you progress through the book, you'll discover backpropagation-an efficient way to calculate the gradients of weight parameters-and study multilayer perceptrons and their limitations, before, finally, implementing a three-layer neural network and calculating multidimensional arrays. By the end of the book, you'll have the knowledge to apply the relevant technologies in deep learning.
