Argilla is a collaboration platform for AI engineers and domain experts that require high-quality outputs, full data ownership, and overall efficiency.
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Updated
May 24, 2024 - Python
Argilla is a collaboration platform for AI engineers and domain experts that require high-quality outputs, full data ownership, and overall efficiency.
🌊 A Human-in-the-Loop workflow for creating HD images from text
Power Tools for AI Engineers With Deadlines
Everything you need about Active Learning (AL).
The data scientist's open-source choice to scale, assess and maintain natural language data. Treat training data like a software artifact.
VR driving 🚙 + eye tracking 👀 simulator based on CARLA for driving interaction research
Semi-automatic tool for manual segmentation of multi-spectral and geo-spatial imagery.
A Universal Deep Reinforcement Learning Framework
DataCLUE: 数据为中心的NLP基准和工具包
Interesting resources related to Explainable Artificial Intelligence, Interpretable Machine Learning, Interactive Machine Learning, Human in Loop and Visual Analytics.
RootPainter: Deep Learning Segmentation of Biological Images with Corrective Annotation
A Preferential Bayesian optimization library for C++/Python [SIGGRAPH 2017]
(Engineering) Toward human-in-the-loop AI: Enhancing deep reinforcement learning via real-time human guidance for autonomous driving
Open Source Human in the Loop platform for anyone to run their own private Mechanical Turk.
RootPainter3D: Interactive-machine-learning enables rapid and accurate contouring for radiotherapy
JOAN is an software package that allows to perform human-in-the loop experiments in the open source driving simulator CARLA. JOAN facilitates communication between human input devices and CARLA, the implementation of haptic feedback, systematically storing experiment data, and the automatic execution of experiments with multiple experimental con…
An agent with human in the loop that can search the web for information while bypassing bot detection for private sites.
Machines and people collaborating together through Jupyter notebooks.
Codes for the EMNLP 2020 paper -- "FIND: Human-in-the-loop Debugging Deep Text Classifiers"
Python-based GUI to collect Feedback of Chemist in Molecules
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