Model explanation provides the ability to interpret the effect of the predictors on the composition of an individual score.

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

Keras 101: A simple Neural Network for House Pricing regression

MEME: Generating RNN Model Explanations via Model Extraction

Awesome PrivEx: Privacy-Preserving Explainable AI (PPXAI)

A School for All Seasons on Trustworthy Machine Learning

💷 💵 💶 A ML project containing web scraping, NLP and some classification model evaluation

The Codebase for Causal Proxy Model

Replacing a Black-box model by a Global Single Tree Approximation

Python implementation of the goldeneye algorithm to investigate how classifiers utilise the structure of a dataset.

A proof-of-concept on how to install and use Torchserve in various mode

Modeling Plasmodium falciparum Diagnostic Test Sensitivity using Machine Learning with Histidine-Rich Protein 2 Variants

Descriptive mAchine Learning EXplanations

Code for "High-Precision Model-Agnostic Explanations" paper. A follow up to LIME model.

主要包含ModelHelper和NLPHelper，其中ModelHelper主要有特征选择、超参数搜索、模型解释和模型融合等，NLPHelper则是进一步封装了NLP一些常用的操作，常用的网络结构以及几个NLP的任务

Predicting Churn Probability for Telecom Customers and deploying the prediction model with Streamlit

Official Website of https://github.com/tamlhp/awesome-privex