👶 Technical concepts explained in layman terms! git.io/eli5

A set of tools for leveraging pre-trained embeddings, active learning and model explainability for effecient document classification

Build a Web App called Menara to Predict, Forecast House Prices and search GreatSchools in California - Bay Area

ELIH: Explain Machine Learning predictions like I'm a human

understand Genaro Network in 1 minute

Graduation Project - Sentiment Mining

E-Commerce Comment Classification with Logistic Regression and LDA model

A telegram channel parser + binary text classifier utilizing a simple logistic regression model

This problem is a typical Classification Machine Learning task. Building various classifiers by using the following Machine Learning models: Logistic Regression (LR), Decision Tree (DT), Random Forest (RF), XGBoost (XGB), Light GBM and Support Vector Machines with RBF kernel.

This is a repository for reproducibility purposes. In this research, a large number of datasets were used to create different ML models, which were then explained by XAI measures. Seeking to identify situations where XAI measures agreed or disagreed with each other.

explain anything

How does Word2Vec work ?

Machine Learning Feature-Importance Using SHAP and eli5

Learning to represent text using Word2Vec

This project aims to explore satellite image dataset in order to create a CNN model for wildfire prediction problem. Explainability with ELI5 and GradCAM could be an interesting integration to be tested.

2022년 1학기 개인 프로젝트 : 뇌졸증 환자 예측 모델·분석

Exploring feature contributions to outliers, feature importances, and image recognition features

Binary to Decimal Encoder-Decoder using RNN with tensorflow

The aim of the project is to analyze the TMDB Prediction Dataset.