Showing 621-640 of 1,001 projects
Texar is a toolkit for machine learning, NLP, and text generation in TensorFlow, part of the CASL project.
Open source neural machine translation library in Torch, focused on deep learning for natural language processing.
This GitHub repository provides a Bootcamp for dealing with unstructured data like reverse image search, audio search, and NLP.
ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators for deep learning and NLP tasks
A comprehensive resource for learning machine learning and deep learning using Python and popular libraries.
TorchIO is a Python library for efficient medical image preprocessing and data augmentation for AI applications.
Curated list of resources for building autonomous vehicles and self-driving car technology
A multitask challenge for NLP that tests various AI models and tools.
A curated list of AutoDL resources and an in-depth analysis for developers interested in automated deep learning and neural architecture search.
A comprehensive collection of resources for model quantization research and optimization.
An extensible deep learning library that leverages JAX for high-performance ML research and production use cases.
Run Mixtral-8x7B language models on Colab or consumer desktops with offloading capabilities.
A dataset of annotated 3D object videos for training computer vision and augmented reality models.
A collection of pre-trained, state-of-the-art AI models for the ailia SDK, supporting a wide range of computer vision and natural language processing tasks.
Tangent is a Python library for source-to-source debuggable automatic differentiation.
A comprehensive TensorFlow & Deep Learning tutorial for developers.
A curated collection of ICCV conference papers, code, and interpretations for computer vision developers.
A simple, powerful, and efficient API for building deep learning models in Python.
An open-source library for deep learning on satellite and aerial imagery using Python and PyTorch.
Jupyter notebooks for learning and using the Keras deep learning library
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