Ar kodu EXTRA58,04 cena tikai €
64,49 €
Math for Deep Learning
58,04 € 
- Mēs nosūtīsim 10-14 darba dienu laikā.
Math for Deep Learning provides the essential math you need to understand deep learning discussions, explore more complex implementations, and better use the deep learning toolkits.With Math for Deep Learning, you'll learn the essential mathematics used by and as a background for deep learning. You’ll work through Python examples to learn key deep learning related topics in probability, statistics, linear algebra, differential calculus, and matrix calculus as well as how to implement data flow…
58.04
2025-06-02 08:00:00
/https://libri-media.knygos-static.lt/26cec903-4e94-44fd-800c-7ba4e2998ec0/1)
- Autors: Ronald T. Kneusel
- Izdevējs Random House LCC US
- Gads: 2021
- ISBN-10 : 1718501900
- ISBN-13 : 9781718501904
- Formāts: 17.7 x 23.2 x 2.4 cm, minkšti viršeliai
- Valoda: Anglų
- Extra -10% atlaide, ievadot kodu: EXTRA
Atsauksmes
Apraksts
Math for Deep Learning provides the essential math you need to understand deep learning discussions, explore more complex implementations, and better use the deep learning toolkits.With Math for Deep Learning, you'll learn the essential mathematics used by and as a background for deep learning.
You’ll work through Python examples to learn key deep learning related topics in probability, statistics, linear algebra, differential calculus, and matrix calculus as well as how to implement data flow in a neural network, backpropagation, and gradient descent. You’ll also use Python to work through the mathematics that underlies those algorithms and even build a fully-functional neural network.
In addition you’ll find coverage of gradient descent including variations commonly used by the deep learning community: SGD, Adam, RMSprop, and Adagrad/Adadelta.
10 EXTRA % atlaide
58,04 €
64,49 €
Mēs nosūtīsim 10-14 darba dienu laikā.
Kupona kods: EXTRA
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Derīgs tikai pirkumiem tiešsaistē.
- Autors: Ronald T. Kneusel
- Izdevējs Random House LCC US
- Gads: 2021
- ISBN-10: 1718501900
- ISBN-13: 9781718501904
- Formāts 17.7 x 23.2 x 2.4 cm, minkšti viršeliai
- Valoda: Anglų
Math for Deep Learning provides the essential math you need to understand deep learning discussions, explore more complex implementations, and better use the deep learning toolkits.
With Math for Deep Learning, you'll learn the essential mathematics used by and as a background for deep learning.
You’ll work through Python examples to learn key deep learning related topics in probability, statistics, linear algebra, differential calculus, and matrix calculus as well as how to implement data flow in a neural network, backpropagation, and gradient descent. You’ll also use Python to work through the mathematics that underlies those algorithms and even build a fully-functional neural network.
In addition you’ll find coverage of gradient descent including variations commonly used by the deep learning community: SGD, Adam, RMSprop, and Adagrad/Adadelta.
With Math for Deep Learning, you'll learn the essential mathematics used by and as a background for deep learning.
You’ll work through Python examples to learn key deep learning related topics in probability, statistics, linear algebra, differential calculus, and matrix calculus as well as how to implement data flow in a neural network, backpropagation, and gradient descent. You’ll also use Python to work through the mathematics that underlies those algorithms and even build a fully-functional neural network.
In addition you’ll find coverage of gradient descent including variations commonly used by the deep learning community: SGD, Adam, RMSprop, and Adagrad/Adadelta.
Atsauksmes