Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!
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Updated
Oct 19, 2024 - HTML
Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!
All about explainable AI, algorithmic fairness and more
User documentation for KServe.
In the wild extraction of entities that are found using Flair and displayed using a very elegant front-end.
Explainable AI Tooling (XAI). XAI is used to discover and explain a model's prediction in a way that is interpretable to the user. Relevant information in the dataset, feature-set, and model's algorithms are exposed.
Counterfactual SHAP: a framework for counterfactual feature importance
Generating global explanations from local ones
XAI-Analytics is a tool that opens the black-box of machine learning. It helps the user to understand the decision-making process of machine learning models.
Explainable AI: From Simple Rules to Complex Generative Models
Concise summaries of key papers in responsible AI.
This repository contains the code of a website to label the commentary for Reinforcement Learning decisions in Pong and Maze environment.
Explainable Speaker Recognition system
Implementing text classification algorithms using the 20 newsgroups datasets, with python
Code of experiments implemented in the paper "Explainability of Predictive Process Monitoring results: Techniques, Experiments and Lessons Learned", comparing XAI methods at different granularities (global/local) with different settings on predictive process monitoring outcomes using process mining event logs
In this article, the factors affecting BERT's transferability is explained through visualizations
We aim to analyze and comment on the psychological impact that the pandemic of COVID-19 has had on the world. Using Explainable AI, we extract the importance of factors contributing to stress and give an overview of what a country needs to improve on, to better handle its next pandemic.
Explainable AI for Healthcare
A scoring system for explainability
📈 [CHI 2023] Results of the statistical analysis applied to the UTA11 guide.
Repository for "Endogenous Macrodynamics in Algorithmic Recourse" (Altmeyer et al., 2023)
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