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Neural networks. Part 5, Introduction to real-world machine learning /
"Neural networks form the foundation for deep learning, the most advanced and popular machine learning technique in use today. This course provides an introduction to neural networks. It begins with an overview of a neural network's basic concepts and building blocks - neurons, weights, ac...
| Clasificación: | Libro Electrónico |
|---|---|
| Otros Autores: | , , |
| Formato: | Electrónico Video |
| Idioma: | Inglés |
| Publicado: |
[Place of publication not identified] :
O'Reilly,
[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 Staglianò, Alessandra, |e speaker. | |
| 245 | 1 | 0 | |a Neural networks. |n Part 5, |p Introduction to real-world machine learning / |c with Alessandra Staglianò, Angie Ma, and Gary Willis. |
| 246 | 3 | 0 | |a Introduction to real-world machine learning |
| 264 | 1 | |a [Place of publication not identified] : |b O'Reilly, |c [2017] | |
| 300 | |a 1 online resource (1 streaming video file (43 min., 16 sec.)) | ||
| 336 | |a two-dimensional moving image |b tdi |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 337 | |a video |b v |2 rdamedia | ||
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| 511 | 0 | |a Presenters, Alessandra Staglianò, Angie Ma, and Gary Willis. | |
| 500 | |a Title from title screen (viewed September 28, 2017). | ||
| 500 | |a Date of publication taken from resource description page. | ||
| 500 | |a "Part 5 of 6." | ||
| 520 | |a "Neural networks form the foundation for deep learning, the most advanced and popular machine learning technique in use today. This course provides an introduction to neural networks. It begins with an overview of a neural network's basic concepts and building blocks - neurons, weights, activations, and layers - before explaining how to train one using gradient descent. The optimization technique is explained with a visual example and different issues such as parameter initialization and model validation are discussed. The course covers the different types of neural network architectures, explains the differences between them, and illustrates practical applications for each. Because training a neural network can be very slow, the course will offer up some tricks for speeding up the process and improving results. The course ends with a review of the history of this fascinating field, from its origin to its fall, and then its subsequent rise in modern days. Requirements include a clear understanding of supervised learning and optimization."--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. | |
| 650 | 0 | |a Artificial intelligence. | |
| 650 | 6 | |a Réseaux neuronaux (Informatique) | |
| 650 | 6 | |a Apprentissage automatique. | |
| 650 | 6 | |a Intelligence artificielle. | |
| 650 | 7 | |a artificial intelligence. |2 aat | |
| 650 | 7 | |a Artificial intelligence. |2 fast |0 (OCoLC)fst00817247 | |
| 650 | 7 | |a Machine learning. |2 fast |0 (OCoLC)fst01004795 | |
| 650 | 7 | |a Neural networks (Computer science) |2 fast |0 (OCoLC)fst01036260 | |
| 700 | 1 | |a Ma, Angie, |e speaker. | |
| 700 | 1 | |a Willis, Gary, |e speaker. | |
| 856 | 4 | 0 | |u https://learning.oreilly.com/videos/~/9781492023975/?ar |z Texto completo (Requiere registro previo con correo institucional) |
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