Topic: eli5 Goto Github
Some thing interesting about eli5
Some thing interesting about eli5
eli5,Graduation Project - Sentiment Mining
User: aimvoma
eli5,ELI5/15/25 Documentation Paradigm
User: akhilburle
Home Page: http://www.eli5-15-25.org/
eli5,Build a Web App called Menara to Predict, Forecast House Prices and search GreatSchools in California - Bay Area
User: akthammomani
eli5,na podstawie kursu "Matrix - poznaj reguΕy gry", stworzonego przez DataWorkshop
User: beatabb
eli5,Exploring feature contributions to outliers, feature importances, and image recognition features
Organization: datadolittle
eli5,How does Word2Vec work ?
User: dhingratul
eli5,Binary to Decimal Encoder-Decoder using RNN with tensorflow
User: dhingratul
eli5,Learning to represent text using Word2Vec
User: dhingratul
eli5,understand Genaro Network in 1 minute
Organization: genaronetwork
eli5,A set of tools for leveraging pre-trained embeddings, active learning and model explainability for effecient document classification
User: hellisotherpeople
Home Page: https://huggingface.co/spaces/Hellisotherpeople/Interpretable_Text_Classification_And_Clustering
eli5,Classifying different books that are semantically close based on their name, then analyzing the misclassified segments by XAI
User: hosnaa
eli5,Using Deep Learning and other Machine Learning models to predict if someone has diabetes
User: jarred13
eli5,A xgboost predictor of Los Angeles house price
User: jokerdii
Home Page: https://jokerdii.github.io/Predicting-Airbnb-House-Price/
eli5,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. Proposing a new measure of XAI called eXirt.
User: josesousaribeiro
eli5,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.
User: josesousaribeiro
eli5, 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.
User: ksharma67
eli5,Choosing strong features for classification purpose of edible and poisonous mushrooms.
User: maciej-zieniewicz
eli5,Social studies lab dedicated to preferences between NA and EU in board games
User: makcfd
eli5,The aim of the project is to analyze the TMDB Prediction Dataset.
User: pranaykankariya97
eli5,Machine Learning Feature-Importance Using SHAP and eli5
User: raymondj-pace
eli5,π π π° Capstone ML project incorporating web scraping, regression modelling and novel use of the ELI5 package to obtain a used car value breakdown
User: rgdavies92
eli5,A telegram channel parser + binary text classifier utilizing a simple logistic regression model
User: samalyarov
eli5,2022λ 1νκΈ° κ°μΈ νλ‘μ νΈ : λμ‘Έμ¦ νμ μμΈ‘ λͺ¨λΈΒ·λΆμ
User: shinho123
eli5,πΆ Technical concepts explained in layman terms! git.io/eli5
User: swapagarwal
Home Page: https://swapagarwal.github.io/awesome-eli5/
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
User: vahadruya
eli5,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.
User: vedantyetekar
eli5,E-Commerce Comment Classification with Logistic Regression and LDA model
User: vincent27hugh
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