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PyTorch Recipes

A Problem-Solution Approach

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Éditeur :

Apress


Paru le : 2019-01-28



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Description




Get up to speed with the deep learning concepts of Pytorch using a problem-solution approach. Starting with an introduction to PyTorch, you'll get familiarized with tensors, a type of data structure used to calculate arithmetic operations and also learn how they operate. You will then take a look at probability distributions using PyTorch and get acquainted with its concepts. Further you will dive into transformations and graph computations with PyTorch. Along the way you will take a look at common issues faced with neural network implementation and tensor differentiation, and get the best solutions for them. 

Moving on to algorithms; you will learn how PyTorch works with supervised and unsupervised algorithms. You will see how convolutional neural networks, deep neural networks, and recurrent neural networks work using PyTorch. In conclusion you will get acquainted with natural language processing and text processing using PyTorch.


What You Will Learn
Master tensor operations for dynamic graph-based calculations using PyTorchCreate PyTorch transformations and graph computations for neural networksCarry out supervised and unsupervised learning using PyTorch Work with deep learning algorithms such as CNN and RNNBuild LSTM models in PyTorch Use PyTorch for text processing 
Who This Book Is For


Readers wanting to dive straight into programming PyTorch.
Pages
184 pages
Collection
n.c
Parution
2019-01-28
Marque
Apress
EAN papier
9781484242575
EAN PDF
9781484242582
Informations sur l'ebook
Nombre pages copiables
1
Nombre pages imprimables
18
Taille du fichier
15432 Ko
Ce livre est accessible aux handicaps Voir les informations sur l'accessibilité
Prix
46,34 €
EAN EPUB
9781484242582
Informations sur l'ebook
Nombre pages copiables
1
Nombre pages imprimables
18
Taille du fichier
15759 Ko
Ce livre est accessible aux handicaps Voir les informations sur l'accessibilité
Prix
46,34 €

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