PyTorch Recipes
Format: Print Book
ISBN: 9781484242575
Tax included.
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.
What You Will Learn
- Master tensor operations for dynamic graph-based calculations using PyTorch
- Create PyTorch transformations and graph computations for neural networks
- Carry out supervised and unsupervised learning using PyTorch
- Work with deep learning algorithms such as CNN and RNN
- Build LSTM models in PyTorch
- Use PyTorch for text processing
Who This Book Is For
Readers wanting to dive straight into programming PyTorch.
Publication Year: 2019
Imprint: Apress
Format: P
Weight (Gram): 320