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refine tool naming (#582)
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remove all parenthesis for unification purposes.
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@zhimin-z
zhimin-z authored Sep 4, 2024
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Expand Up @@ -88,11 +88,11 @@ Please review our [CONTRIBUTING.md](https://github.com/EthicalML/awesome-product
* [AdvBox](https://github.com/advboxes/AdvBox) ![](https://img.shields.io/github/stars/advboxes/AdvBox.svg?style=social) - A toolbox to generate adversarial examples that fool neural networks in PaddlePaddle, PyTorch, Caffe2, MxNet, Keras, TensorFlow, and Advbox can benchmark the robustness of machine learning models.
* [Adversarial DNN Playground](https://github.com/QData/AdversarialDNN-Playground) ![](https://img.shields.io/github/stars/QData/AdversarialDNN-Playground.svg?style=social) - think [TensorFlow Playground](https://playground.tensorflow.org), but for Adversarial Examples! A visualization tool designed for learning and teaching - the attack library is limited in size, but it has a nice front-end to it with buttons you can press!
* [AdverTorch](https://github.com/BorealisAI/advertorch) ![](https://img.shields.io/github/stars/BorealisAI/advertorch.svg?style=social) - library for adversarial attacks / defenses specifically for PyTorch.
* [ART](https://github.com/Trusted-AI/adversarial-robustness-toolbox) ![](https://img.shields.io/github/stars/Trusted-AI/adversarial-robustness-toolbox.svg?style=social) - ART (Adversarial Robustness Toolbox) provides tools that enable developers and researchers to defend and evaluate Machine Learning models and applications against the adversarial threats of Evasion, Poisoning, Extraction, and Inference.
* [Artificial Adversary](https://github.com/airbnb/artificial-adversary) ![](https://img.shields.io/github/stars/airbnb/artificial-adversary.svg?style=social) AirBnB's library to generate text that reads the same to a human but passes adversarial classifiers.
* [Counterfit](https://github.com/Azure/counterfit) ![](https://img.shields.io/github/stars/Azure/counterfit.svg?style=social) - Counterfit is a command-line tool and generic automation layer for assessing the security of machine learning systems.
* [Factool](https://github.com/GAIR-NLP/factool) ![](https://img.shields.io/github/stars/GAIR-NLP/factool.svg?style=social) - Factool is a tool augmented framework for detecting factual errors of texts generated by large language models.
* [Foolbox](https://github.com/bethgelab/foolbox) ![](https://img.shields.io/github/stars/bethgelab/foolbox.svg?style=social) - Foolbox is a Python toolbox to create adversarial examples that fool neural networks in PyTorch, TensorFlow, and JAX.
* [Adversarial Robustness Toolbox (ART))](https://github.com/Trusted-AI/adversarial-robustness-toolbox) ![](https://img.shields.io/github/stars/Trusted-AI/adversarial-robustness-toolbox.svg?style=social) - ART provides tools that enable developers and researchers to defend and evaluate Machine Learning models and applications against the adversarial threats of Evasion, Poisoning, Extraction, and Inference.
* [MIA](https://github.com/spring-epfl/mia) ![](https://img.shields.io/github/stars/spring-epfl/mia.svg?style=social) - A library for running membership inference attacks (MIA) against machine learning models.
* [NeMo Guardrails](https://github.com/NVIDIA/NeMo-Guardrails) ![](https://img.shields.io/github/stars/NVIDIA/NeMo-Guardrails.svg?style=social) - NeMo Guardrails is an open-source toolkit for easily adding programmable guardrails to LLM-based conversational systems.
* [OpenAttack](https://github.com/thunlp/OpenAttack) ![](https://img.shields.io/github/stars/thunlp/OpenAttack.svg?style=social) - OpenAttack is a Python-based textual adversarial attack toolkit, which handles the whole process of textual adversarial attacking, including preprocessing text, accessing the victim model, generating adversarial examples and evaluation.
Expand All @@ -104,9 +104,9 @@ Please review our [CONTRIBUTING.md](https://github.com/EthicalML/awesome-product
* [Deequ](https://github.com/awslabs/deequ) ![](https://img.shields.io/github/stars/awslabs/deequ.svg?style=social) - A library built on top of Apache Spark for defining "unit tests for data", which measure data quality in large datasets.
* [Deep Anomaly Detection with Outlier Exposure](https://github.com/hendrycks/outlier-exposure) ![](https://img.shields.io/github/stars/hendrycks/outlier-exposure.svg?style=social) - Outlier Exposure (OE) is a method for improving anomaly detection performance in deep learning models. [Paper](https://arxiv.org/pdf/1812.04606.pdf)
* [PyOD](https://github.com/yzhao062/pyod) ![](https://img.shields.io/github/stars/yzhao062/pyod.svg?style=social) - A Python Toolbox for Scalable Outlier Detection (Anomaly Detection).
* [SUOD (Scalable Unsupervised Outlier Detection)](https://github.com/yzhao062/SUOD) ![](https://img.shields.io/github/stars/yzhao062/SUOD.svg?style=social) - An Acceleration System for Large-scale Anomaly/Outlier Detection.
* [Tensorflow Data Validation (TFDV)](https://github.com/tensorflow/data-validation) ![](https://img.shields.io/github/stars/tensorflow/data-validation.svg?style=social) - Library for exploring and validating machine learning data.
* [SUOD](https://github.com/yzhao062/SUOD) ![](https://img.shields.io/github/stars/yzhao062/SUOD.svg?style=social) - SUOD (Scalable Unsupervised Outlier Detection) is an acceleration system for large-scale anomaly/outlier detection.
* [TextAttack](https://github.com/QData/TextAttack) ![](https://img.shields.io/github/stars/QData/TextAttack.svg?style=social) - TextAttack is a Python framework for adversarial attacks, data augmentation, and model training in NLP.
* [TFDV](https://github.com/tensorflow/data-validation) ![](https://img.shields.io/github/stars/tensorflow/data-validation.svg?style=social) - TFDV (Tensorflow Data Validation) is a library for exploring and validating machine learning data.
* [TODS](https://github.com/datamllab/tods) ![](https://img.shields.io/github/stars/datamllab/tods.svg?style=social) - TODS is a full-stack automated machine learning system for outlier detection on multivariate time-series data.


Expand Down Expand Up @@ -159,7 +159,7 @@ Please review our [CONTRIBUTING.md](https://github.com/EthicalML/awesome-product
* [brat rapid annotation tool](https://github.com/nlplab/brat) ![](https://img.shields.io/github/stars/nlplab/brat.svg?style=social) - Web-based text annotation tool for Named-Entity-Recogntion task.
* [cleanlab](https://github.com/cleanlab/cleanlab) ![](https://img.shields.io/github/stars/cleanlab/cleanlab.svg?style=social) - Python library for data-centric AI. Can automatically: find mislabeled data, detect outliers, estimate consensus + annotator-quality for multi-annotator datasets, suggest which data is best to (re)label next.
* [COCO Annotator](https://github.com/jsbroks/coco-annotator) ![](https://img.shields.io/github/stars/jsbroks/coco-annotator.svg?style=social) - Web-based image segmentation tool for object detection, localization and keypoints
* [Computer Vision Annotation Tool (CVAT)](https://github.com/cvat-ai/cvat) ![](https://img.shields.io/github/stars/cvat-ai/cvat.svg?style=social) - OpenCV's web-based annotation tool for both VIDEOS and images for computer algorithms.
* [CVAT](https://github.com/cvat-ai/cvat) ![](https://img.shields.io/github/stars/cvat-ai/cvat.svg?style=social) - CVAT (Computer Vision Annotation Tool) is OpenCV's web-based annotation tool for both videos and images for computer algorithms.
* [Doccano](https://github.com/doccano/doccano) ![](https://img.shields.io/github/stars/doccano/doccano.svg?style=social) - Open source text annotation tools for humans, providing functionality for sentiment analysis, named entity recognition, and machine translation.
* [Gretel Synthetics](https://github.com/gretelai/gretel-synthetics) ![](https://img.shields.io/github/stars/gretelai/gretel-synthetics.svg?style=social) - Gretel Synthetics is a synthetic data generators for structured and unstructured text, featuring differentially private learning.
* [ImageTagger](https://github.com/bit-bots/imagetagger) ![](https://img.shields.io/github/stars/bit-bots/imagetagger.svg?style=social) - Image labelling tool with support for collaboration, supporting bounding box, polygon, line, point labelling, label export, etc.
Expand Down Expand Up @@ -509,9 +509,9 @@ Please review our [CONTRIBUTING.md](https://github.com/EthicalML/awesome-product
* [Catalyst](https://github.com/catalyst-team/catalyst) ![](https://img.shields.io/github/stars/catalyst-team/catalyst.svg?style=social) - High-level utils for PyTorch DL & RL research. It was developed with a focus on reproducibility, fast experimentation and code/ideas reusing.
* [ClearML](https://github.com/allegroai/clearml) ![](https://img.shields.io/github/stars/allegroai/clearml.svg?style=social) - Auto-Magical Experiment Manager & Version Control for AI (previously Trains).
* [CodaLab](https://github.com/codalab/codalab-worksheets) ![](https://img.shields.io/github/stars/codalab/codalab-worksheets.svg?style=social) - CodaLab Worksheets is a collaborative platform for reproducible research that allows researchers to run, manage, and share their experiments in the cloud. It helps researchers ensure that their runs are reproducible and consistent.
* [Data Version Control (DVC)](https://github.com/iterative/dvc) ![](https://img.shields.io/github/stars/iterative/dvc.svg?style=social) - A git fork that allows for version management of models.
* [Deepkit](https://github.com/deepkit/deepkit-ml) ![](https://img.shields.io/github/stars/deepkit/deepkit-ml.svg?style=social) - An open-source platform and cross-platform desktop application to execute, track, and debug modern machine learning experiments.
* [Dolt](https://github.com/dolthub/dolt) ![](https://img.shields.io/github/stars/dolthub/dolt.svg?style=social) - Dolt is a SQL database that you can fork, clone, branch, merge, push and pull just like a git repository.
* [DVC](https://github.com/iterative/dvc) ![](https://img.shields.io/github/stars/iterative/dvc.svg?style=social) - DVC (Data Version Control) is a git fork that allows for version management of models.
* [Flor](https://github.com/ucbrise/flor) ![](https://img.shields.io/github/stars/ucbrise/flor.svg?style=social) - Easy to use logger and automatic version controller made for data scientists who write ML code.
* [Guild AI](https://github.com/guildai/guildai) ![](https://img.shields.io/github/stars/guildai/guildai.svg?style=social) - Open source toolkit that automates and optimizes machine learning experiments.
* [Hangar](https://github.com/tensorwerk/hangar-py) ![](https://img.shields.io/github/stars/tensorwerk/hangar-py.svg?style=social) - Version control for tensor data, git-like semantics on numerical data with high speed and efficiency.
Expand Down Expand Up @@ -617,7 +617,7 @@ Please review our [CONTRIBUTING.md](https://github.com/EthicalML/awesome-product
* [Sematic](https://github.com/sematic-ai/sematic) ![](https://img.shields.io/github/stars/sematic-ai/sematic.svg?style=social) - Platform to build resource-intensive pipelines with simple Python.
* [Skaffold](https://github.com/GoogleContainerTools/skaffold) ![](https://img.shields.io/github/stars/GoogleContainerTools/skaffold.svg?style=social) - Skaffold is a command line tool that facilitates continuous development for Kubernetes applications. You can iterate on your application source code locally then deploy to local or remote Kubernetes clusters.
* [Streaming](https://github.com/mosaicml/streaming) ![](https://img.shields.io/github/stars/mosaicml/streaming.svg?style=social) - A Data Streaming Library for Efficient Neural Network Training.
* [Tensorflow Extended (TFX)](https://github.com/tensorflow/tfx) ![](https://img.shields.io/github/stars/tensorflow/tfx.svg?style=social) - Production oriented configuration framework for ML based on TensorFlow, incl. monitoring and model version management.
* [TFX](https://github.com/tensorflow/tfx) ![](https://img.shields.io/github/stars/tensorflow/tfx.svg?style=social) - Tensorflow Extended (TFX) is a production oriented configuration framework for ML based on TensorFlow, incl. monitoring and model version management.
* [veScale](https://github.com/volcengine/veScale) ![](https://img.shields.io/github/stars/volcengine/veScale.svg?style=social) - veScale is a PyTorch native LLM training framework.


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