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The PyTorch Tutorials repository is a collection of educational resources that provides step-by-step guidance on building, training, and deploying neural networks using the PyTorch framework. It covers the complete machine learning workflow, from data loading and model definition through optimization loops and model persistence, with dedicated guides for distributed training, model fine-tuning, and deployment. The tutorials offer practical demonstrations of adapting pre-trained models to new tasks through transfer learning, scaling training across multiple GPUs or machines using PyTorch's dis
Practical PyTorch is a collection of deep learning tutorials and guides focused on implementing recurrent neural networks. The project provides practical code for building sequence models and sequence-to-sequence architectures using the PyTorch framework. The repository covers the implementation of models for neural machine translation, character-level text generation, and text classification. It includes examples for transforming input sequences into output sequences for machine translation and synthesizing new text. The project also extends to sequence data prediction and time series analy
This repository serves as a comprehensive collection of reference implementations for the PyTorch machine learning library. It provides practical examples for building, training, and deploying deep learning models, functioning as a toolkit for developers to explore neural network architectures and training workflows. The project distinguishes itself by offering concrete demonstrations of complex machine learning operations, ranging from computer vision tasks like object detection and depth estimation to the training of large-scale transformer models. These examples illustrate how to implement
Albumentations is an image augmentation library and computer vision preprocessing tool designed to expand datasets for deep learning models. It provides a collection of transformations that modify pixel values and spatial geometry to increase the diversity of training samples and improve model generalization. The library supports both 2D image augmentation and 3D volumetric data augmentation. It handles a variety of labels alongside images, ensuring that bounding boxes, keypoints, and segmentation masks remain accurately aligned when spatial transformations are applied. The tool incorporates
An IPython Notebook tutorial on deep learning for natural language processing, including structure prediction.
The main features of rguthrie3/deeplearningfornlpinpytorch are: Deep Learning Frameworks, Tutorials.
Open-source alternatives to rguthrie3/deeplearningfornlpinpytorch include: spro/practical-pytorch — Practical PyTorch is a collection of deep learning tutorials and guides focused on implementing recurrent neural… pytorch/tutorials — The PyTorch Tutorials repository is a collection of educational resources that provides step-by-step guidance on… pytorch/examples — This repository serves as a comprehensive collection of reference implementations for the PyTorch machine learning… albu/albumentations — Albumentations is an image augmentation library and computer vision preprocessing tool designed to expand datasets for… andersbll/deeppy — Deep learning in Python. amznlabs/amazon-dsstne — Amazon DSSTNE is a machine learning toolkit and sparse tensor network library designed for deep learning models with…