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Introduction to deep learning : concepts and fundamentals /
"Deep learning neural networks have driven breakthrough results in computer vision, speech processing, machine translation, and reinforcement learning. As a result, neural networks have become an essential part of any data scientist's toolkit. This course explains what neural networks are,...
| Clasificación: | Libro Electrónico |
|---|---|
| Formato: | Electrónico Video |
| Idioma: | Inglés |
| Publicado: |
[Place of publication not identified] :
O'Reilly Media,
[2017]
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| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
MARC
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| 100 | 1 | |a Graesser, Laura, |e on-screen presenter. | |
| 245 | 1 | 0 | |a Introduction to deep learning : |b concepts and fundamentals / |c with Laura Graesser. |
| 264 | 1 | |a [Place of publication not identified] : |b O'Reilly Media, |c [2017] | |
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| 511 | 0 | |a Presenter, Laura Graesser. | |
| 520 | |a "Deep learning neural networks have driven breakthrough results in computer vision, speech processing, machine translation, and reinforcement learning. As a result, neural networks have become an essential part of any data scientist's toolkit. This course explains what neural networks are, why they are powerful algorithms, and why they have a particular structure. It begins by introducing the core components of a neural network (i.e., nodes, weights, biases, activation functions, and layers). Along the way, you'll learn about the backpropagation algorithm and how neural networks learn."--Resource description page | ||
| 590 | |a O'Reilly |b O'Reilly Online Learning: Academic/Public Library Edition | ||
| 650 | 0 | |a Neural networks (Computer science) | |
| 650 | 0 | |a Machine learning. | |
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| 650 | 6 | |a Réseaux neuronaux (Informatique) | |
| 650 | 6 | |a Apprentissage automatique. | |
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| 650 | 7 | |a Neural networks (Computer science) |2 fast |0 (OCoLC)fst01036260 | |
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