PyTorch Recipes

PyTorch Recipes

Mishra, Pradeepta

29,11 €(IVA inc.)

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 probabilistic programming 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 transfer learning and deep q-learning algorithms work with PyTorch. Moving on, you will learn to implement convolutional neural nets and Elman’s recurrent neural networks in PyTorch. In conclusion you will get acquainted with natural language processing and text processing using PyTorch.

What You Will Learn
  • Master probabilistic programming using PyTorch
  • Create PyTorch transformations and graph computations 
  • Carry out supervised and unsupervised learning using PyTorch 
  • Work with deep q-learning algorithms 
  • Build convolutional neural nets and recurrent neural networks
Who This Book Is For

Readers wanting to dive straight into programming PyTorch.

  • ISBN: 978-1-4842-4257-5
  • Editorial: Apress
  • Encuadernacion: Rústica
  • Páginas: 160
  • Fecha Publicación: 28/03/2019
  • Nº Volúmenes: 1
  • Idioma: Inglés