Showing 81-100 of 266 projects
Deep learning library for point clouds in 3D space
A comprehensive collection of deep learning resources including courses, case studies, and interview questions.
A comprehensive CSS library of system font stacks for every modern operating system.
Catalyst is an accelerated deep learning R&D library for Python that supports a variety of AI and machine learning use cases.
A curated list of resources and projects related to quantum machine learning, algorithms, and frameworks.
A semantic router system for deploying and managing a mixture of AI models at the cloud, data center, and edge.
An index of algorithms for learning causality with data, useful for vibe coders working on AI-powered applications.
MTEB is a benchmark for evaluating and comparing text embedding models across multiple tasks and languages.
An extensible NLP framework for building powerful text processing and analysis applications in Python.
A machine learning toolkit for time series analysis and classification in Python.
Open-source pre-training model framework in PyTorch with a pre-trained model zoo for natural language processing tasks.
A collection of Python tutorials covering a wide range of topics from computer vision to network security.
A curated list of awesome resources on transformers in time series analysis, forecasting, and more.
This repository provides a roadmap and code samples for machine learning, deep learning, and related AI technologies.
A curated list of articles related to deep learning applied to music and audio processing.
This GitHub repository contains projects for the Udacity Self-Driving Car Engineer Nanodegree, focusing on computer vision, deep learning, and autonomous vehicle technology.
Deep learning-based image classification system for danbooru images using TensorFlow.
A comprehensive collection of papers and datasets for 3D point cloud processing, useful for developers working on autonomous driving and computer vision.
A repository with papers, code, and experiments using deep learning for time series forecasting.
An AI-powered tool for training supervised models without manual labeling, using foundation models and multimodal learning.
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