miyamotok0105/pytorch_handbook
pytorch_handbook
This handbook provides practical code examples for implementing various neural network architectures using PyTorch. It takes raw data as input and produces trained neural network models for tasks like image classification, object detection, and sequence prediction. This resource is designed for developers and researchers who want to build and experiment with deep learning models using the PyTorch framework.
113 stars. No commits in the last 6 months.
Use this if you are a developer or researcher looking for concrete, hands-on PyTorch code examples to build neural networks for various deep learning tasks.
Not ideal if you are looking for a conceptual introduction to deep learning theory without code, or if you prefer a framework other than PyTorch.
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113
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Jupyter Notebook
License
MIT
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Last pushed
Feb 23, 2023
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