Speed up state-of-the-art ViT models in Hugging Face 🤗 up to 2300% (25x times faster ) with Databricks, Nvidia, and Spark NLP 🚀

Pytorch is a powerful open-source deep-learning framework that is quickly gaining popularity among researchers and developers

An image dataset contains specially selected digital images intended to help train, test, and evaluate an artificial intelligence (AI) or machine learning (ML)

Flexible and scalable template based on PyTorch Lightning and Hydra. Efficient workflow and reproducibility for rapid ML experiments.

PyTorch has gained a reputation as a research-focused framework, and these are the Best PyTorch Datasets for Building Deep Learning Models available today.

With torchvision datasets, developers can train and test their machine learning models on a range of tasks, such as image classification and object detection.

Frameworks for object detection and computer vision tasks are indeed numerous. This article attempts to highlight the available frameworks for object detection.

Binary classification NN is used with the sigmoid activation function on its final layer together with BCE loss. The final layer size should be 1.

Explore the seamless implementation of automatic filtering using PyTorch and the Transformers library.

Explore the unique aspects of VAEs, which separate them from traditional autoencoders by enabling data generation through sampling from a distribution

Pytorch requires manual management of tensor contiguity in many cases. This automates that.