sgrvinod/Deep-Tutorials-for-PyTorch
A collection of in-depth tutorials for implementing deep learning models from research papers using PyTorch.
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This repository contains comprehensive tutorials for implementing deep learning models from scratch using PyTorch. Each tutorial focuses on a specific application or architecture by reproducing results from a research paper. Topics include image captioning with attention mechanisms, sequence labeling with CRFs, single-shot object detection (SSD), super-resolution, and transformer architectures. The tutorials also teach foundational concepts such as encoder-decoder architectures, transfer learning, and multi-task learning.
Frequently asked
- What is sgrvinod/Deep-Tutorials-for-PyTorch?
- A collection of in-depth tutorials for implementing deep learning models from research papers using PyTorch.
- Is Deep-Tutorials-for-PyTorch open source?
- Yes — sgrvinod/Deep-Tutorials-for-PyTorch is an open-source project tracked on heatdrop.
- How popular is Deep-Tutorials-for-PyTorch?
- sgrvinod/Deep-Tutorials-for-PyTorch has 1.6k stars on GitHub.
- Where can I find Deep-Tutorials-for-PyTorch?
- sgrvinod/Deep-Tutorials-for-PyTorch is on GitHub at https://github.com/sgrvinod/Deep-Tutorials-for-PyTorch.