51,11 €
63,89 €
Math for Deep Learning
51,11 € 
- Išsiųsime per 10–14 d.d.
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…
51.11
2025-06-29 23:59:00
/https://libri-media.knygos-static.lt/26cec903-4e94-44fd-800c-7ba4e2998ec0/1)
- Autorius: Ronald T. Kneusel
- Leidėjas: Random House LCC US
- Metai: 2021
- ISBN-10: 1718501900
- ISBN-13: 9781718501904
- Formatas: 17.7 x 23.2 x 2.4 cm, minkšti viršeliai
- Kalba: Anglų
- Extra -20 % nuolaida šiai knygai su kodu ENG20
Atsiliepimai
Aprašymas
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.
EXTRA 20 % nuolaida
51,11 €
63,89 €
Išsiųsime per 10–14 d.d.
Kupono kodas: ENG20
Akcija baigiasi už 3d.07:18:06
Nuolaidos kodas galioja perkant nuo 10 €. Nuolaidos nesumuojamos.
- Autorius: Ronald T. Kneusel
- Leidėjas: Random House LCC US
- Metai: 2021
- ISBN-10: 1718501900
- ISBN-13: 9781718501904
- Formatas: 17.7 x 23.2 x 2.4 cm, minkšti viršeliai
- Kalba: 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.
Atsiliepimai