This project is an educational resource and comprehensive guide for implementing and deploying deep learning models using the PyTorch framework. It provides a structured learning curriculum consisting of tutorials and notebooks that cover neural network architectures, data pipelines, and model optimization across multiple AI domains. The curriculum includes practical implementation guides for building convolutional networks, transformers, and recurrent models. It specifically focuses on workflows for computer vision, including image classification, object detection, and segmentation, as well
Accelerate is a framework for high-performance array computing that provides a domain-specific language for expressing complex mathematical and parallel computations. By utilizing a declarative programming interface, it allows users to define high-level array transformations that are automatically translated into optimized machine code for diverse hardware architectures. The system distinguishes itself through a modular architecture that decouples high-level array operations from hardware-specific instructions. It employs just-in-time compilation and kernel fusion to transform programs into e
R frontend for Spark
The main features of amplab-extras/sparkr-pkg are: Parallel Computing.
Open-source alternatives to amplab-extras/sparkr-pkg include: datawhalechina/thorough-pytorch — This project is an educational resource and comprehensive guide for implementing and deploying deep learning models… acceleratehs/accelerate — Accelerate is a framework for high-performance array computing that provides a domain-specific language for expressing… davisvaughan/furrr. shenwei356/rush. vertica/ddr — Standard API for Distributed Data Structures in R. vertica/distributedr — Distributed R is a scalable high-performance platform for the R language. It enables and accelerates large scale…
