Code for "High-Precision Model-Agnostic Explanations" paper. A follow up to LIME model.
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Updated
Dec 5, 2018 - Jupyter Notebook
Code for "High-Precision Model-Agnostic Explanations" paper. A follow up to LIME model.
Course project for 6.869: automatic summarization for neural net interpretability
Visualizing an XGBoost model in R using a sunburst plot (using inTrees)
Using LIME and SHAP for model interpretability of Machine Learning Black-box models.
Will They Pay? A machine learning solution to understand mobile app user payment behavior
Pytorch Implementation of recent visual attribution methods for model interpretability
Class Activation Map (CAM) Visualizations in PyTorch.
Human Factors in Model Interpretability: Industry Practices, Challenges, and Needs
A machine learning project developing classification models to predict COVID-19 diagnosis in paediatric patients.
Interpretability and Fairness in Machine Learning
An Explainable AI technique introduced in the paper Axiomatic Attribution for Deep Networks
Code for "Investigating and Simplifying Masking-based Saliency Methods for Model Interpretability" (https://arxiv.org/abs/2010.09750)
The project provides explanation of what SHAP is and how it can be used to interpret model. Also contains Notebook with detail on model interpretability method SHAP and code implementation on Heart disease dataset.
pytorch实现Grad-CAM和Grad-CAM++,可以可视化任意分类网络的Class Activation Map (CAM)图,包括自定义的网络;同时也实现了目标检测faster r-cnn和retinanet两个网络的CAM图;欢迎试用、关注并反馈问题...
Implementation of the Grad-CAM algorithm in an easy-to-use class, optimized for transfer learning projects and written using Keras and Tensorflow 2.x
Official repository for the paper "Instance-wise Causal Feature Selection for Model Interpretation" (CVPRW 2021)
Used the Functional API to built custom layers and non-sequential model types in TensorFlow, performed object detection, image segmentation, and interpretation of convolutions. Used generative deep learning including Auto Encoding, VAEs, and GANs to create new content.
The "keras-translator" helps you to understand a keras trained model.
AI to Predict Yield in Aeroponics
A python script for basic data cleaning/manipulation and modelling based on the open source House Sales Advanced Regression Techniques(Kaggle)
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