Deep Learning with PyTorch

Deep Learning with PyTorch involves the practical application of deep learning principles using the open-source PyTorch framework. Celebrated for its Python-first design, flexibility offered by dynamic computational graphs, and robust GPU-accelerated tensor computations, PyTorch provides an intuitive yet powerful platform for researchers and developers. It streamlines the entire process of building, training, and deploying complex neural network architectures, from initial prototyping and experimentation to production-level implementation, making it a leading choice for a wide range of artificial intelligence tasks.

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1.

1.1.

1.1.1.

1.1.2.

1.1.3.

1.2.

1.2.1.

1.2.2.

1.2.2.1.

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1.2.2.4.

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1.4.4.

1.5.

1.5.1.

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1.5.2.

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1.6.

1.6.1.

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1.7.1.

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1.7.3.

1.7.3.1.

1.7.3.2.

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1.7.3.4.

1.7.4.

1.7.4.1.

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1.7.4.3.

1.7.5.

1.7.5.1.

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1.7.5.3.

1.7.5.4.

1.7.5.5.

1.8.

1.8.1.

1.8.1.1.

1.8.1.2.

1.8.2.

1.8.2.1.

1.8.2.2.

1.8.2.3.

1.8.3.

1.8.3.1.

1.8.3.2.

1.8.3.3.

1.8.4.

1.8.4.1.

1.8.4.2.

1.8.4.3.

1.8.5.

1.8.5.1.

1.8.5.2.

1.8.5.3.

1.8.5.4.

1.8.5.5.

1.8.6.

1.8.6.1.

1.8.6.2.

1.8.6.3.

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2. PyTorch Fundamentals