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140 public repositories
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🔅 Shapash makes Machine Learning models transparent and understandable by everyone
Updated
Mar 11, 2022
Jupyter Notebook
Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, and security.
Updated
Feb 10, 2021
Jupyter Notebook
Lime client built using flutter
Updated
May 31, 2018
Dart
Python implementation of two low-light image enhancement techniques via illumination map estimation
Updated
Jul 18, 2021
Python
Updated
Mar 9, 2022
Jupyter Notebook
C# LIME protocol implementation
Multicycles.org aggregates on one map, more than 200 share vehicles like bikes, scooters, mopeds and cars. Demo APP for the Data Flow API, see
https://flow.fluctuo.com
ProjectFNF is a mostly quality-of-life engine for Friday Night Funkin. It is easy to understand and is super flexible.
Application of the LIME algorithm by Marco Tulio Ribeiro, Sameer Singh, Carlos Guestrin to the domain of time series classification
Updated
Apr 6, 2021
Python
Adversarial Attacks on Post Hoc Explanation Techniques (LIME/SHAP)
Updated
Mar 12, 2022
Jupyter Notebook
Simple C# Keylogger (Keyboard Layout)
Short overview over the components used by Lime Scooters fleet
Updated
Aug 1, 2021
Assembly
Local Interpretable (Model-agnostic) Visual Explanations - model visualization for regression problems and tabular data based on LIME method. Available on CRAN
A library for drawing graphics on the console screen
Updated
Jan 2, 2020
Crystal
ProjectFNF 2.0, based on Psych Engine
Implementation of the paper, "LIME: Low-Light Image Enhancement via Illumination Map Estimation", which is for my graduation thesis.
Updated
Aug 12, 2021
Python
General-purpose library for extracting interpretable models from Multi-Agent Reinforcement Learning systems
In this work, we propose a deterministic version of Local Interpretable Model Agnostic Explanations (LIME) and the experimental results on three different medical datasets shows the superiority for Deterministic Local Interpretable Model-Agnostic Explanations (DLIME).
Updated
Oct 19, 2021
Jupyter Notebook
Techniques & resources for training interpretable ML models, explaining ML models, and debugging ML models.
Updated
Mar 12, 2022
Jupyter Notebook
FastAI Model Interpretation with LIME
Updated
Feb 7, 2019
Jupyter Notebook
2D OpenGL Render Library in haxe/lime - old origin version
Updated
Oct 27, 2020
Haxe
Segway Ninebot serial communication analyzer (ESCx such as Voi, Circ / Flash, Bolt, Dott, Jump, Tier...)
Updated
Sep 2, 2019
JavaScript
This repository will have all my gnuradio exsamples
Updated
May 27, 2021
Python
Overview of different model interpretability libraries.
Updated
May 11, 2021
Jupyter Notebook
Build a Web App called Menara to Predict, Forecast House Prices and search GreatSchools in California - Bay Area
Updated
Jul 28, 2021
Jupyter Notebook
An example of how the LIME algorithm can be used to provide real-world insight into the decision processes of a 'black-box' machine learning algorithm - in this case a Radom Forest regressor.
Updated
Feb 19, 2019
Jupyter Notebook
A Flask LIME explainer app for fine-grained sentiment classification.
Updated
Nov 16, 2021
Python
This repository introduces different Explainable AI approaches and demonstrates how they can be implemented with PyTorch and torchvision. Used approaches are Class Activation Mappings, LIMA and SHapley Additive exPlanations.
Updated
Sep 5, 2019
Jupyter Notebook
Gets a list of closest lime scooters to a location, or notifies you if one is close
Updated
May 2, 2019
Python
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