January 2025
Intermediate to advanced
698 pages
16h 48m
English
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4.2 Building and Training Neural Networks with PyTorch
In PyTorch, neural networks are constructed using the powerful torch.nn module. This module serves as a comprehensive toolkit for building deep learning models, offering a wide array of pre-implemented components essential for creating sophisticated neural architectures. These components include:
- Fully connected layers (also known as dense layers)
- Convolutional layers for image processing tasks
- Recurrent layers for sequence modeling
- Various activation functions (e.g., ReLU, Sigmoid, Tanh)
- Loss functions for different types of learning tasks
One of PyTorch's key strengths lies in its modular and intuitive design philosophy. This approach allows developers to define custom models with great flexibility ...
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