Getting Started with PyTorch

In this chapter, we’ll explore PyTorch, a leading deep learning library in Python.

We go over several operations that are useful for understanding how neural networks are built using PyTorch. Besides tensor operations, we will also explore how to train different types of neural networks. Specifically, we will focus on feedforward, recurrent, long short-term memory (LSTM), and 1D convolutional networks.

In later chapters, we will also cover other types of neural networks, such as transformers. Here, we will use synthetic data for demonstrative purposes, which will help us showcase both the implementation and theory behind each model.

Upon completing this chapter, you will have gained a robust understanding of PyTorch, equipping you with the tools for more advanced deep learning projects.

In this chapter, we will cover the following recipes:

• Installing PyTorch
• Basic operations in PyTorch
• Advanced operations in PyTorch
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