Classification and clustering texts

It's a little knowledge base using some scripts that I faced in my professional life.

Advanced Machine Learning course taught at Linköping University. Learned how Machine Learning models can be utilized to solve regression and classification problems within the AI field.

This project aims to predict the number of bikes using regression models., following the CRISP-DM approach

Multivariate Regression to predict sales of Used Cars

As part of a group project, I developed separate regression models using R to predict the daily number of batteries and robberies in Chicago using four different datasets. I tested interactive and second-order terms and used stepwise feature selection to find the best model with the given data. I tested several potential models using cross-valid…

Capstone project for my Master's degree. In it, I developed some machine learning models to predict the heat of formation for materials containing 1–3 components.

Had the aspirations for the future and sense of capability of children at-risk improved under the influence of military service, and in what manner.

A data science project to predict house prices in King County

first business data analysis - factors affecting student satisfaction and bank clients

r and rstudio scripts

The purpose of this project is to demonstrate my ability to clean raw dataset, construct regression models, and communicate the findings in a reproducible fashion.

Prediction of House Prices based on Linear Regression Model

Execução dos códigos do Livro Machine Learning with R Packt

Car Price and Heart Failure prediction using Generalized Linear Models (GLMs)

For my Data Analytics subject I studied about car consumption habits depending on different factors collected in a survey made by Smartme Analytics.

Ejemplos y guias practicas de estadistica- anova,lm,glm, multinom, survival

Function for improving regression ceofficient plots

The model tries to predict the number of sales calls that a maintenance company might be receiving based on climatic and weather conditions. The age of the car and the duration of connection with the company are also to be considered. The model tries to explore the important factors which are significant and help in getting a high accuracy of pr…