ProphitBet is a Machine Learning Soccer Bet prediction application. It analyzes the form of teams, computes match statistics and predicts the outcomes of a match using Advanced Machine Learning (ML) methods. The supported algorithms in this application are Neural Networks, Random Forests & Ensembl Models.

Pytorch implementation of various neural network interpretability methods

Learning clinical-decision rules with interpretable models.

Official code of the CVPR 2022 paper "Proto2Proto: Can you recognize the car, the way I do?"

Experiments with experimental rule-based models to go along with imodels.

Explaining black boxes with a SMILE: Statistical Mode-agnostic Interpretability with Local Explanations

CVPR 2021 | Metrics for evaluating interpretability methods.

🦠 DeepDecipher: An open source API to MLP neurons

Initial Exploratory Works on Knowledge Tracing in Transformer Based Language Models

Metrics for evaluating interpretability methods.

Code for the paper "Comparing Feature Importance and Rule Extraction for Interpretability on Text Data", XAIE @ ICPR 2022

A repository to study the interpretability of time series networks(LSTM)

Repository for the journal article 'SHAMSUL: Systematic Holistic Analysis to investigate Medical Significance Utilizing Local interpretability methods in deep learning for chest radiography pathology prediction'

This repository will focus on interpretability of ML algorithms. From linear regression to transformers..

A curated list of awesome machine learning interpretability resources.

Interpreting Timeseries using Local Interpretation methods