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The Top 23 Jupyter Notebook Explainable Ai Open Source Projects

Open source projects categorized as Jupyter Notebook Explainable Ai
Categories > Explainable Ai
Categories > Data Processing > Jupyter Notebook
Tensorwatch ⭐ 3,333
Debugging, monitoring and visualization for Python Machine Learning and Data Science
dependent packages 1total releases 14most recent commit 8 months agopypi tensorwatch} Downloads
Imodels ⭐ 1,229
Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).
dependent packages 4total releases 44most recent commit 4 months agopypi imodels} Downloads
Responsible Ai Toolbox ⭐ 1,187
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.
dependent packages 8total releases 6most recent commit 11 days agopypi raiutils} Downloads
Transformers Interpret ⭐ 1,090
Model explainability that works seamlessly with 🤗 transformers. Explain your transformers model in just 2 lines of code.
dependent packages 2total releases 36most recent commit 8 months agopypi transformers-interpret} Downloads
Omnixai ⭐ 674
OmniXAI: A Library for eXplainable AI
dependent packages 3total releases 14most recent commit 8 months agopypi omnixai} Downloads
Daam ⭐ 545
Diffusion attentive attribution maps for interpreting Stable Diffusion.
total releases 16most recent commit 3 months ago
Ml_privacy_meter ⭐ 501
Privacy Meter: An open-source library to audit data privacy in statistical and machine learning algorithms.
total releases 1most recent commit 4 months ago
Transformer Mm Explainability ⭐ 490
[ICCV 2021- Oral] Official PyTorch implementation for Generic Attention-model Explainability for Interpreting Bi-Modal and Encoder-Decoder Transformers, a novel method to visualize any Transformer-based network. Including examples for DETR, VQA.
most recent commit a year ago
Quantus ⭐ 460
Quantus is an eXplainable AI toolkit for responsible evaluation of neural network explanations
dependent packages 1total releases 27most recent commit 3 months agopypi quantus} Downloads
Machine_learning_tutorials ⭐ 421
Code, exercises and tutorials of my personal blog ! 📝
most recent commit 4 years ago
Explainx ⭐ 375
Explainable AI framework for data scientists. Explain & debug any blackbox machine learning model with a single line of code. We are looking for co-authors to take this project forward. Reach out @ [email protected]
total releases 56most recent commit 3 months ago
Datascience_artificialintelligence_utils ⭐ 369
Examples of Data Science projects and Artificial Intelligence use-cases
most recent commit 9 months ago
Cnn Exposed ⭐ 157
🕵️‍♂️ Interpreting Convolutional Neural Network (CNN) Results.
most recent commit 5 years ago
Diffusers Interpret ⭐ 143
Diffusers-Interpret 🤗🧨🕵️‍♀️: Model explainability for 🤗 Diffusers. Get explanations for your generated images.
total releases 11most recent commit 2 years ago
Path_explain ⭐ 134
A repository for explaining feature attributions and feature interactions in deep neural networks.
total releases 7most recent commit 2 years ago
Hierarchical Dnn Interpretations ⭐ 119
Using / reproducing ACD from the paper "Hierarchical interpretations for neural network predictions" 🧠 (ICLR 2019)
total releases 7most recent commit 3 years ago
Seggradcam ⭐ 83
SEG-GRAD-CAM: Interpretable Semantic Segmentation via Gradient-Weighted Class Activation Mapping
most recent commit 7 months ago
Pytorch_explain ⭐ 80
PyTorch Explain: Logic Explained Networks in Python.
total releases 22most recent commit 9 months ago
Zennit Crp ⭐ 80
An eXplainable AI toolkit with Concept Relevance Propagation and Relevance Maximization
total releases 11most recent commit 3 months ago
Deep Explanation Penalization ⭐ 74
Code for using CDEP from the paper "Interpretations are useful: penalizing explanations to align neural networks with prior knowledge" https://arxiv.org/abs/1909.13584
most recent commit 3 years ago
Survshap ⭐ 65
SurvSHAP(t): Time-dependent explanations of machine learning survival models
most recent commit 3 months ago
Machine Learning For High Risk Applications Book ⭐ 60
Official code repo for the O'Reilly Book - Machine Learning for High-Risk Applications
most recent commit a year ago
Representer_point_selection ⭐ 53
code release for Representer point Selection for Explaining Deep Neural Network in NeurIPS 2018
most recent commit 3 years ago
The 6 Most Depended On Jupyter Notebook Explainable Ai Open Source Projects
Imodels ⭐ 1,229
Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).
dependent packages 4total releases 44latest release October 05, 2023most recent commit 4 months agopypi imodels} Downloads
Omnixai ⭐ 674
OmniXAI: A Library for eXplainable AI
dependent packages 3total releases 14latest release June 10, 2022most recent commit 8 months agopypi omnixai} Downloads
Tensorwatch ⭐ 3,333
Debugging, monitoring and visualization for Python Machine Learning and Data Science
dependent packages 1total releases 14latest release March 04, 2020most recent commit 8 months agopypi tensorwatch} Downloads
Quantus ⭐ 460
Quantus is an eXplainable AI toolkit for responsible evaluation of neural network explanations
dependent packages 1total releases 27latest release December 05, 2023most recent commit 3 months agopypi quantus} Downloads
The 10 Latest Releases In Jupyter Notebook Explainable Ai Open Source Projects
Quantus ⭐ 460
Quantus is an eXplainable AI toolkit for responsible evaluation of neural network explanations
dependent packages 1total releases 27latest release December 05, 2023most recent commit 3 months agopypi quantus} Downloads
Imodels ⭐ 1,229
Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).
dependent packages 4total releases 44latest release October 05, 2023most recent commit 4 months agopypi imodels} Downloads
Biaslyze ⭐ 28
The NLP Bias Identification Toolkit
total releases 9latest release August 25, 2023most recent commit 7 months ago
Fg Clustering ⭐ 26
Explainability for Random Forest Models.
total releases 9latest release April 12, 2023most recent commit 7 months ago
Daam ⭐ 545
Diffusion attentive attribution maps for interpreting Stable Diffusion.
total releases 16latest release December 16, 2022most recent commit 3 months ago
Zennit Crp ⭐ 80
An eXplainable AI toolkit with Concept Relevance Propagation and Relevance Maximization
total releases 11latest release November 01, 2022most recent commit 3 months ago
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