Implementation of LIME focused on producing user-centric local explanations for image classifiers.

This repository contains the Python scripts that I have written and run to execute a series of analytic model developments using datasets taken from the book "The Elements of Statistical Elements" by Hastie, Tibshirani, Friedman

A solid foundational understanding of XAI, primarily emphasizing how XAI methodologies can expose latent biases in datasets and reveal valuable insights.

A tool for classifying an image into a disaster type, utilizing Python

A library for drawing graphics on the console screen

🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models

C# LIME protocol implementation

Unpack, Pack & Resign files encrypted with the 1st version of "Lime" encryption.

Scripts for generating SHAP & LIME explainations and their corresponding plots

This repository provides the training codes to classify aerial images using a custom-built model (transfer learning with InceptionResNetV2 as the backbone) and explainers to explain the predictions with LIME and GradCAM on an interface that lets you upload or paste images for classification and see visual explanations.

Code for submitted paper

Multicycles.org aggregates on one map, more than 300 share vehicles like bikes, scooters, mopeds and cars. Demo APP for the Data Flow API, see https://flow.fluctuo.com

Montimage AI Platform (MAIP) provides users with easy access to AI services developed by Montimage, through a friendly and intuitive interface.

A shader engine made using Lime and GLSL.

Multi-classification of ocular diseases using ODIR-5K and uses explainable AI methods to improve the transparency of computer aided diagnostic systems.

Qt-DAB, a general software DAB (DAB+) decoder with a (slight) focus on showing the signal

This study aimed to assess whether machine learning algorithms would outperform traditional modeling in developing a cesarean delivery prediction model among gravidas with morbid obesity (body mass index of ≥40 kg/m2) to determine whether a primary cesarean delivery may be beneficial.

Java client for the lime.co trader api

Tasks for Advanced Machine Learning Technologies Course @ ITMO University.

Scoring model for financial company - all files