Catalogue of Tools & Metrics for Trustworthy AI

These tools and metrics are designed to help AI actors develop and use trustworthy AI systems and applications that respect human rights and are fair, transparent, explainable, robust, secure and safe.

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Objective Transparency & explainability
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embedchain

TechnicalUnited StatesUploaded on Apr 22, 2024
Data platform for LLMs - Load, index, retrieve and sync any unstructured data

Objective(s)

Transparency & explainability

Related lifecycle stage(s)

Build & interpret model

deeplearningexamples

TechnicalUnited StatesUploaded on Apr 22, 2024
State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.

Objective(s)

Transparency & explainability

Related lifecycle stage(s)

Build & interpret model

chainer

TechnicalUploaded on Apr 22, 2024
A flexible framework of neural networks for deep learning

Objective(s)

Transparency & explainability

Related lifecycle stage(s)

Build & interpret model

xlnet

TechnicalUnited StatesUploaded on Apr 22, 2024
XLNet: Generalized Autoregressive Pretraining for Language Understanding

Objective(s)

Transparency & explainability

Related lifecycle stage(s)

Build & interpret modelPlan & design

mit-deep-learning

TechnicalUnited KingdomUploaded on Apr 22, 2024
Tutorials, assignments, and competitions for MIT Deep Learning related courses.

Objective(s)

Transparency & explainability

Related lifecycle stage(s)

Operate & monitorDeployVerify & validateBuild & interpret modelCollect & process dataPlan & design

learn-python3

TechnicalFinlandUploaded on Apr 22, 2024
Jupyter notebooks for teaching/learning Python 3

Objective(s)

Transparency & explainability

Related lifecycle stage(s)

Build & interpret model

turicreate

TechnicalUnited StatesUploaded on Apr 22, 2024
Turi Create simplifies the development of custom machine learning models.

Objective(s)

Transparency & explainability

Related lifecycle stage(s)

Operate & monitorDeployVerify & validateBuild & interpret modelCollect & process dataPlan & design

machine-learning-cheat-sheet

TechnicalSpainUploaded on Apr 22, 2024
Classical equations and diagrams in machine learning

Objective(s)

Transparency & explainability

Related lifecycle stage(s)

Operate & monitorDeployVerify & validateBuild & interpret modelCollect & process dataPlan & design

pyaudioanalysis

TechnicalGreeceUploaded on Apr 22, 2024
Python Audio Analysis Library: Feature Extraction, Classification, Segmentation and Applications

Objective(s)

Transparency & explainability

Related lifecycle stage(s)

Operate & monitorDeployVerify & validateBuild & interpret modelCollect & process dataPlan & design

tensorrt

TechnicalUnited StatesUploaded on Apr 22, 2024
NVIDIA® TensorRT™, an SDK for high-performance deep learning inference, includes a deep learning inference optimizer and runtime that delivers low latency and high throughput for inference applications.

Objective(s)

Transparency & explainability

Related lifecycle stage(s)

Build & interpret modelPlan & design

ValidMind

TechnicalUnited StatesUploaded on Apr 18, 2024
An end-to-end model risk management platform that automates model documentation and dramatically simplifies AI model validation.

Objective(s)

Transparency & explainability

Related lifecycle stage(s)

Verify & validateBuild & interpret modelCollect & process data

The Citrusx Platform

TechnicalProceduralIsraelUploaded on Apr 11, 2024
Citrusx offers a multifaceted solution to connect all stakeholders in the company through an SDK, user-friendly UI, and automated reporting system.

Objective(s)

Transparency & explainability

Related lifecycle stage(s)

Operate & monitorVerify & validateCollect & process data

zamba

TechnicalUploaded on Apr 2, 2024
A Python package for identifying 42 kinds of animals, training custom models, and estimating distance from camera trap videos

Objective(s)

Transparency & explainability

Related lifecycle stage(s)

Build & interpret model

yopo-you-only-propagate-once

TechnicalUnited StatesUploaded on Apr 2, 2024
Code for our nips19 paper: You Only Propagate Once: Accelerating Adversarial Training Via Maximal Principle

Objective(s)

Transparency & explainability

Related lifecycle stage(s)

Build & interpret model

yolov3-tf2

TechnicalUnited StatesUploaded on Apr 2, 2024
YoloV3 Implemented in Tensorflow 2.0

Objective(s)

Transparency & explainability

Related lifecycle stage(s)

Build & interpret model

vespa

TechnicalUploaded on Apr 2, 2024
The open big data serving engine. https://vespa.ai

Objective(s)

Transparency & explainability

Related lifecycle stage(s)

Operate & monitorDeployVerify & validateBuild & interpret modelCollect & process dataPlan & design

ultralytics

TechnicalUnited StatesUploaded on Apr 2, 2024
NEW - YOLOv8 🚀 in PyTorch > ONNX > OpenVINO > CoreML > TFLite

Objective(s)

Transparency & explainability

Related lifecycle stage(s)

Operate & monitorDeployVerify & validateBuild & interpret modelCollect & process dataPlan & design

trustworthyai

TechnicalUploaded on Apr 2, 2024
trustworthy AI related projects

Objective(s)

Transparency & explainability

tflearn

TechnicalUploaded on Apr 2, 2024
Deep learning library featuring a higher-level API for TensorFlow.

Objective(s)

Transparency & explainability

Related lifecycle stage(s)

DeployBuild & interpret modelCollect & process dataPlan & design

tensorwatch

TechnicalUnited StatesUploaded on Apr 2, 2024
Debugging, monitoring and visualization for Python Machine Learning and Data Science

Objective(s)

Transparency & explainability

Related lifecycle stage(s)

Build & interpret modelPlan & design
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Disclaimer: The tools and metrics featured herein are solely those of the originating authors and are not vetted or endorsed by the OECD or its member countries. The Organisation cannot be held responsible for possible issues resulting from the posting of links to third parties' tools and metrics on this catalogue. More on the methodology can be found at https://oecd.ai/catalogue/faq.