《动手学深度学习》:面向中文读者、能运行、可讨论。中英文版被70多个国家的500多所大学用于教学。
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Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
🤗 The largest hub of ready-to-use datasets for AI models with fast, easy-to-use and efficient data manipulation tools
CVAT is a leading data annotation platform for image, video, audio, and 3D datasets. It offers open-source, cloud, and enterprise products, as well as labeling services, with AI-assisted labeling, quality assurance, team collaboration, analytics, and developer APIs.
- video-annotation
- computer-vision
- computer-vision-annotation
- image-annotation
pix2tex: Using a ViT to convert images of equations into LaTeX code.
A MNIST-like fashion product database. Benchmark :point_down:
Low-code framework for building custom LLMs, neural networks, and other AI models
Cleanlab's open-source library is the standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.
- weak-supervision
- data-cleaning
- data-quality
- noisy-labels
Fast and Accurate ML in 3 Lines of Code
A system for quickly generating training data with weak supervision
- machine-learning
- ai
- weak-supervision
- labeling
[IROS 2020] se(3)-TrackNet: Data-driven 6D Pose Tracking by Calibrating Image Residuals in Synthetic Domains
- robotics
- tracking
- computer-vision
- pose-estimation
Open, source-backed catalog of computer-use agents: reviewed papers, GUI models, datasets, benchmarks, tools, and reusable JSONL/SQLite data.
- agent-evaluation
- agentic-ai
- ai-agents
- awesome
AgML is a centralized framework for agricultural machine learning. AgML provides access to public agricultural datasets for common agricultural deep learning tasks, with standard benchmarks and pretrained models, as well the ability to generate synthetic data and annotations.
- deep-learning
- agriculture
- pytorch
- dataset
Kaapana is an open source toolkit for state of the art platform provisioning in the field of medical data analysis. The applications comprise AI-based workflows and federated learning scenarios with a focus on radiological and radiotherapeutic imaging. The name Kaapana comes from the Hawaiian word kaʻāpana, meaning "distributor" or "part".
- imaging
- ai
- cloud-computing
- medical-imaging
Meta Self-learning for Multi-Source Domain Adaptation: A Benchmark
- text-recognition
- ocr-recognition
- domain-adaptation
- multi-source-domain-adaptation
Automated Testing for Set-Top Boxes and Smart TVs
- python
- test-automation
- set-top-box
- remote-control