This repository contains different scenarios and its solutions with R programming.
-
Updated
Dec 29, 2021 - R
This repository contains different scenarios and its solutions with R programming.
This repository includes my House Prices Multi-Variate Linear Regression-Flatiron School Module 2 Project. In this project I made use of the OSEMN methodology incorporating packages such as Pandas, NumPy, Matplotlib, Seaborn, and Scikit-Learn.
Personal Finanace Analysis using OSEMN Framework.
Early warning system predicting student grade risk (D/F) using Random Forest — OSEMN pipeline, Flask demo, 83.3% accuracy
Analisi dell'andamento decennale degli indici S&P 500 ed EURO STOXX 50 in Python: notebook Jupyter con pandas e matplotlib, metodologia OSEMN, EDA, outlier detection (IQR) su rendimenti e volumi, con insight di investimento.
In this project, I used the OSEMN data science workflow to obtain, scrub, explore, model, and interpret a King County dataset with a multivariate linear regression to predict the sale price of houses.
Add a description, image, and links to the osemn topic page so that developers can more easily learn about it.
To associate your repository with the osemn topic, visit your repo's landing page and select "manage topics."