Topic: responsible-ai Goto Github
Some thing interesting about responsible-ai
Some thing interesting about responsible-ai
responsible-ai,[AI6101] Introduction to AI & AI Ethics is a core course of MSAI, SCSE, NTU, Singapore. The repository corresponds to the AI6101 of Semester 1, AY2021-2022, starting from 08/2021. The instructors of this course are Prof. Bo An, Prof. Yu Han, and Dr. Melvin Chen.
User: accsrd
responsible-ai,A curated list of awesome academic research, books, code of ethics, data sets, institutes, newsletters, principles, podcasts, reports, tools, regulations and standards related to Responsible AI, Trustworthy AI, and Human-Centered AI.
Organization: athenacore
responsible-ai,Azure Machine Learning と GitHub を利用した MLOps のサンプルコード
Organization: azure
responsible-ai,The Python Risk Identification Tool for generative AI (PyRIT) is an open access automation framework to empower security professionals and machine learning engineers to proactively find risks in their generative AI systems.
Organization: azure
responsible-ai,A "Responsible AI For Developers" hub to help developer audiences (students, entrepreneurs and professionals) discover workshop, events and resources that can help them learn and use Responsible AI concepts and resources effectively in their own projects.
Organization: azure
Home Page: https://aka.ms/rai-hub/website
responsible-ai,Credo AI Lens is a comprehensive assessment framework for AI systems. Lens standardizes model and data assessment, and acts as a central gateway to assessments created in the open source community.
Organization: credo-ai
Home Page: https://credoai-lens.readthedocs.io/en/stable/
responsible-ai,Open-source toolkit to help companies implement responsible AI workflows.
Organization: cylynx
Home Page: https://www.verifyml.com
responsible-ai,An in-depth performance profiling library for machine learning models
Organization: dataresponsibly
responsible-ai,An open-content programming cookbook. A responsible use of AI proof of concept. Collaborative, polyglot and multilingual.
User: dogweather
Home Page: https://forkful.ai
responsible-ai,A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
Organization: ethicalml
Home Page: https://ethicalml.github.io/awesome-production-machine-learning
responsible-ai,Reading list for adversarial perspective and robustness in deep reinforcement learning.
User: ezgikorkmaz
responsible-ai,A Python package to assess and improve fairness of machine learning models.
Organization: fairlearn
Home Page: https://fairlearn.org
responsible-ai,🐢 Open-Source Evaluation & Testing for LLMs and ML models
Organization: giskard-ai
Home Page: https://docs.giskard.ai
responsible-ai,AART: AI-Assisted Red-Teaming with Diverse Data Generation for New LLM-powered Applications
Organization: google-research-datasets
Home Page: https://arxiv.org/abs/2311.08592
responsible-ai,💡 Adversarial attacks on explanations and how to defend them
User: hbaniecki
Home Page: https://doi.org/10.1016/j.inffus.2024.102303
responsible-ai,Checklist for an analysis of various aspects of responsibility of models and data resources
User: hryniewska
Home Page: https://www.sciencedirect.com/science/article/pii/S0031320321002223
responsible-ai, [ICCV 2023 Oral, Best Paper Finalist] ITI-GEN: Inclusive Text-to-Image Generation
Organization: humansensinglab
Home Page: https://czhang0528.github.io/iti-gen
responsible-ai,🤖🛡️🔍🔒🔑 Tiny package designed to support red teams and penetration testers in exploiting large language model AI solutions.
User: hupe1980
Home Page: https://hupe1980.github.io/aisploit/
responsible-ai,PyTorch package to train and audit ML models for Individual Fairness
Organization: ibm
Home Page: https://ibm.github.io/inFairness
responsible-ai,[NeurIPS 2023] Sentry-Image: Detect Any AI-generated Images
Organization: inf-imagine
responsible-ai,Deliver safe & effective language models
Organization: johnsnowlabs
Home Page: http://langtest.org/
responsible-ai,A curated list of explainability-related papers, articles, and resources focused on Large Language Models (LLMs). This repository aims to provide researchers, practitioners, and enthusiasts with insights into the explainability implications, challenges, and advancements surrounding these powerful models.
User: koo-ec
responsible-ai,WOUAF: Weight Modulation for User Attribution and Fingerprinting in Text-to-Image Diffusion Models (CVPR 2024)
User: kylemin
responsible-ai,Référentiel d'évaluation data science responsable et de confiance
Organization: labelialabs
Home Page: https://www.labelia.org/fr/datascience
responsible-ai,Explore/examine/explain/expose your model with the explabox!
User: marcelrobeer
Home Page: https://explabox.readthedocs.io
responsible-ai,This framework aims to assists in the documentation of datasets to promote transparency and help dataset creators and consumers make informed decisions about whether specific datasets meet their needs and what limitations they need to consider
Organization: microsoft
Home Page: https://microsoft.github.io/opendatasheets/
responsible-ai,Responsible AI Toolbox is a suite of tools providing model and data exploration and assessment user interfaces and libraries that enable a better understanding of AI systems. These interfaces and libraries empower developers and stakeholders of AI systems to develop and monitor AI more responsibly, and take better data-driven actions.
Organization: microsoft
Home Page: https://responsibleaitoolbox.ai/
responsible-ai,Python library for implementing Responsible AI mitigations.
Organization: microsoft
Home Page: https://responsible-ai-toolbox-mitigations.readthedocs.io/en/latest/
responsible-ai,Responsible AI Workshop: a series of tutorials & walkthroughs to illustrate how put responsible AI into practice
Organization: microsoft
responsible-ai,Official code repo for the O'Reilly Book - Machine Learning for High-Risk Applications
Organization: ml-for-high-risk-apps-book
responsible-ai,Multi-Calibration & Multi-Accuracy Boosting for R
Organization: mlr-org
responsible-ai,moDel Agnostic Language for Exploration and eXplanation
Organization: modeloriented
Home Page: https://dalex.drwhy.ai
responsible-ai,Carefully curated list of awesome data science resources.
User: natnew
responsible-ai,Oracle Guardian AI Open Source Project is a library consisting of tools to assess fairness/bias and privacy of machine learning models and data sets.
Organization: oracle
Home Page: https://oracle-guardian-ai.readthedocs.io
responsible-ai,In situ interactive widgets for responsible AI 🌱
Organization: pair-code
Home Page: https://pair-code.github.io/farsight/
responsible-ai,Taught by AI genius Andrew NG, this course entails the cutting edge topics such as, How generative AI works including what it can and can't do, Common uses cases such as Reading, Writing, and Chatting, Life Cycle of GenAI projects, Advanced Technology options such as RAG, Fine tunning, and Pre-Training, Implications of GenAI on business & Society.
User: rabbia-hassan
Home Page: https://www.deeplearning.ai/courses/generative-ai-for-everyone/
responsible-ai,A collection of news articles, books, and papers on Responsible AI cases. The purpose is to study these cases and learn from them to avoid repeating the failures of the past.
User: romanlutz
Home Page: https://romanlutz.github.io/ResponsibleAI
responsible-ai,Enforcing fairness in binary and multiclass classification
User: scotthlee
responsible-ai,Data-IQ: Characterizing subgroups with heterogeneous outcomes in tabular data (NeurIPS 2022)
User: seedatnabeel
responsible-ai,Data-SUITE: Data-centric identification of in-distribution incongruous examples (ICML 2022)
User: seedatnabeel
responsible-ai,A detailed summary of "Designing Machine Learning Systems" by Chip Huyen. This book gives you and end-to-end view of all the steps required to build AND OPERATE ML products in production. It is a must-read for ML practitioners and Software Engineers Transitioning into ML.
User: serodriguez68
Home Page: https://www.oreilly.com/library/view/designing-machine-learning/9781098107956/
responsible-ai,Code for the 2023 ICCV paper "VLSlice: Interactive Vision-and-Language Slice Discovery."
User: slymane
Home Page: https://ericslyman.com/vlslice/
responsible-ai,A toolkit that streamlines and automates the generation of model cards
Organization: tensorflow
Home Page: https://www.tensorflow.org/responsible_ai/model_card_toolkit/guide
responsible-ai,Package for evaluating the performance of methods which aim to increase fairness, accountability and/or transparency
Organization: wearepal
Home Page: https://wearepal.ai/EthicML/
responsible-ai,Sample Selection for Fair and Robust Training (NeurIPS 2021)
User: yuji-roh
responsible-ai,FairBatch: Batch Selection for Model Fairness (ICLR 2021)
User: yuji-roh
responsible-ai,FR-Train: A Mutual Information-Based Approach to Fair and Robust Training (ICML 2020)
User: yuji-roh
responsible-ai,Official code of "Discover and Mitigate Unknown Biases with Debiasing Alternate Networks" (ECCV 2022)
User: zhihengli-ur
responsible-ai,Official code of "Discover the Unknown Biased Attribute of an Image Classifier" (ICCV 2021)
User: zhihengli-ur
responsible-ai,Official code of "StyleT2I: Toward Compositional and High-Fidelity Text-to-Image Synthesis" (CVPR 2022)
User: zhihengli-ur
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