6026 Open source projects that are alternatives of or similar to Shap

A lightweight implementation of removal-based explanations for ML models.

Fit interpretable models. Explain blackbox machine learning.

For calculating global feature importance using Shapley values.

ProtoTrees: Neural Prototype Trees for Interpretable Fine-grained Image Recognition, published at CVPR2021

Codebase for "Demystifying Black-box Models with Symbolic Metamodels", NeurIPS 2019.

The code of AAAI 2020 paper "Transparent Classification with Multilayer Logical Perceptrons and Random Binarization".

Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, and security.

🏥 Visualizing Convolutional Networks for MRI-based Diagnosis of Alzheimer’s Disease

Collection of NLP model explanations and accompanying analysis tools

XAI Tutorial for the Explainable AI track in the ALPS winter school 2021

Zennit is a high-level framework in Python using PyTorch for explaining/exploring neural networks using attribution methods like LRP.

Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).

InfiniteBoost: building infinite ensembles with gradient descent

[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.

Adaptive, interpretable wavelets across domains (NeurIPS 2021)

Data generator for Arena - interactive XAI dashboard

Text classification models. Used a submodule for other projects.

Explainable AI framework for data scientists. Explain & debug any blackbox machine learning model with a single line of code.

H2O.ai Machine Learning Interpretability Resources

A collection of infrastructure and tools for research in neural network interpretability.

A Julia package for interpretable machine learning with stochastic Shapley values

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

Human-explainable AI.

A collection of state-of-the-art algorithms for the training, serving and interpretation of Decision Forest models.

Automatic equation building and curve fitting. Runs on Tensorflow. Built for academia and research.

A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning

A collection of tools for reverse engineering neural networks.

Using / reproducing ACD from the paper "Hierarchical interpretations for neural network predictions" 🧠 (ICLR 2019)

Pytorch Implementation of recent visual attribution methods for model interpretability

Library implementing state-of-the-art Concept-based and Disentanglement Learning methods for Explainable AI

Code for the TCAV ML interpretability project

⬛ Python Individual Conditional Expectation Plot Toolbox

This is a comprehensive ML techniques with python: Define the Problem- Specify Inputs & Outputs- Data Collection- Exploratory data analysis -Data Preprocessing- Model Design- Training- Evaluation

Use CNN to detect nodules in LIDC dataset.

MIMIC-Extract:A Data Extraction, Preprocessing, and Representation Pipeline for MIMIC-III

Many Class Activation Map methods implemented in Pytorch for CNNs and Vision Transformers. Including Grad-CAM, Grad-CAM++, Score-CAM, Ablation-CAM and XGrad-CAM

deeplearning.ai , By Andrew Ng, All slide and notebook + data + solutions and video link

This is the code for the "How to Make Word Vectors from Game of Thrones (LIVE) " Siraj Raval on Youtube

High-Resolution Network for Photorealistic Style Transfer

PyTorch for Deep Learning and Computer Vision Course

StructureNet: Hierarchical Graph Networks for 3D Shape Generation

A collection of open-source GPU accelerated Python tools and examples for quantitative analyst tasks and leverages RAPIDS AI project, Numba, cuDF, and Dask.

蚂蚁学Python，微信公众号的代码仓库

Assessing car damage with convolution neural networks for a personal auto claims expedition use case

Code for the NuerIPS'19 paper "Gate Decorator: Global Filter Pruning Method for Accelerating Deep Convolutional Neural Networks"

ZeroCostDL4Mic: A Google Colab based no-cost toolbox to explore Deep-Learning in Microscopy

Face mask detection system using Deep learning.

Notebooks using the Hugging Face libraries 🤗

This Python library makes it easy to display images and videos in a notebook.

This book is geared toward those who already have programming knowledge. It covers topics that include: creation of user interfaces, computer graphics, internet applications, distributed systems, among other issues.

Classifying White Blood Cells with CNNs

Code and slides of my YouTube series called "Audio Signal Proessing for Machine Learning"

Scripts and data for various Vox Media stories and news projects

Trained A Convolutional Neural Network To Play 2048 using Deep-Reinforcement Learning

Stuff I uploaded to share online or to access from a different machine

Magic functions for using Jupyter Notebook with Apache Spark and a variety of SQL databases.

Transformer OCR