Showing 321-340 of 799 projects
A dataset for music analysis and research, with support for deep learning and reproducible research.
An easy-to-use natural language processing library built on the Gluon deep learning framework.
A PyTorch optimizer that adapts the learning rate to reduce the variance of gradients, improving training performance.
Official PyTorch implementation of U-GAT-IT, an unsupervised generative adversarial network for image-to-image translation.
Simplified implementations of deep learning related works for developers interested in AI and machine learning.
Automated architecture search and hyperparameter optimization for PyTorch models.
LibMTL is a PyTorch library for building multi-task learning models for deep learning applications.
A collection of summaries for machine learning research papers, useful for developers interested in AI and deep learning.
An open-source deep learning framework for building, training, and fine-tuning models using physics-ML methods.
A library of scikit-learn compatible categorical variable encoders for machine learning applications.
A PyTorch domain library for building recommendation systems using GPU-accelerated deep learning.
Elegant PyTorch implementation of the Model-Agnostic Meta-Learning (MAML) paper for AI/ML developers.
Blazing-fast GPU compute framework built on Vulkan for advanced data processing use cases.
A Python library for emulating guitar amplifiers using neural networks.
A Keras implementation of CapsNet, a deep learning model for image classification.
This repository provides an educational resource for learning machine learning from scratch using Jupyter Notebooks.
A repository with notes and solutions for common algorithms and interview questions, especially for AI/ML roles.
An intuitive Python library that adds plotting functionality to scikit-learn machine learning models
A general-purpose deep learning backbone for molecular modeling, suitable for AI-focused developers.
A collection of data science related questions and answers for developers.
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