👶 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

Graduation Project - Sentiment Mining

E-Commerce Comment Classification with Logistic Regression and LDA model

understand Genaro Network in 1 minute

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.

How does Word2Vec work ?

Machine Learning Feature-Importance Using SHAP and eli5

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

Learning to represent text using Word2Vec

2022년 1학기 개인 프로젝트 : 뇌졸증 환자 예측 모델·분석

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.

🍎 Translate text to ELI5

This project aims to predict the Taxi-trip duration within NYC based on several factors as predictors. Various combinations of relevant features are explored as iterations. After analysing the dataset, important and necessary features are selected. Several regression models are implemented & evaluated based on R2 & RMSE, & predictions visualised

Binary to Decimal Encoder-Decoder using RNN with tensorflow

Social studies lab dedicated to preferences between NA and EU in board games

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