👶 Technical concepts explained in layman terms! git.io/eli5
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Updated
Oct 26, 2023
👶 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
Graduation Project - Sentiment Mining
E-Commerce Comment Classification with Logistic Regression and LDA 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.
How does Word2Vec work ?
Machine Learning Feature-Importance Using SHAP and eli5
Learning to represent text using Word2Vec
A telegram channel parser + binary text classifier utilizing a simple logistic regression model
2022년 1학기 개인 프로젝트 : 뇌졸증 환자 예측 모델·분석
Binary to Decimal Encoder-Decoder using RNN with tensorflow
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
Medify is a MERN stack app that predicts heart disease using machine learning. Patients can send their medical data to their doctors through the app.
The aim of the project is to analyze the TMDB Prediction Dataset.
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