Fundamentals of deep learning designing next-generation machine intelligence algorithms
With the reinvigoration of neural networks in the 2000s, deep learning has become an extremely active area of research, one that’s paving the way for modern machine learning. In this practical book, author Nikhil Buduma provides examples and clear explanations to guide you through major concepts of...
| Otros Autores: | , |
|---|---|
| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
Beijing, [China] :
O'Reilly
2017.
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| Edición: | First edition |
| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009623415606719 |
Tabla de Contenidos:
- The neural network
- Training feed-forward neural networks
- Implementing neural networks in TensorFlow
- Beyond gradient descent
- Convolutional neural networks
- Embedding and representation learning
- Models for sequence analysis
- Memory augmented neural networks
- Deep reinforcement learning.
