Welcome to the PyTorch practice tutorial! PyTorch is a popular open-source machine learning library for Python, widely used for deep learning applications. This guide will help you get started with PyTorch, covering basic concepts and practical exercises.

Basic Concepts

  • Tensors: The fundamental data structure in PyTorch.
  • Autograd: Automatic differentiation system.
  • NN Modules: Building blocks for neural networks.

Practice Exercises

Here are some exercises to help you practice PyTorch:

  1. Create and manipulate tensors.
  2. Define and train a simple neural network.
  3. Use PyTorch to load and preprocess data.

Example Code

import torch

# Create a tensor
x = torch.tensor([1.0, 2.0, 3.0])

# Perform tensor operations
y = x + 1

print(y)

Further Reading

For more detailed tutorials and documentation, check out our PyTorch Documentation.

Images

  • tensor
  • autograd
  • neural_network

If you have any questions or need further assistance, feel free to reach out to our Community Forum. Happy learning!