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Machine Learning In R ⭐ 144

Workshop (6 hours): preprocessing, cross-validation, lasso, decision trees, random forest, xgboost, superlearner ensembles

Predicting_real_estate_prices_using_scikit Learn ⭐ 59

Predicting Amsterdam house / real estate prices using Ordinary Least Squares-, XGBoost-, KNN-, Lasso-, Ridge-, Polynomial-, Random Forest-, and Neural Network MLP Regression (via scikit-learn)

Supervised Machine Learning ⭐ 15

This repo contains regression and classification projects. Examples: development of predictive models for comments on social media websites; building classifiers to predict outcomes in sports competitions; churn analysis; prediction of clicks on online ads; analysis of the opioids crisis and an analysis of retail store expansion strategies using Lasso and Ridge regressions.

Data Science Portfolio ⭐ 10

Secimtools ⭐ 10

A set of metabolomics tools for use in Galaxy

Data Science Projects ⭐ 8

{PySpark, R, Python}: Several Data Science projects

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