Kaggle challenge asking to predict the final price of each home based on their description/properties.

This is a project developed as part of the Foundations of Data science course at New York University

This is the solution for prediction of the customers with high probability of churn.

Fuel price forecasting

Ejercicio de regresiones por distintos métodos (Mejor Selección de Conjuntos, Selección de pasos hacia adelante, Ridge, LASSO, Elastic Net, Componentes Principales, Mínimos Cuadrados Parciales, etc.)

Linear Regression Models on Montesinho Forest Fire

Data Models in R for Multiple Linear Regression and three models (Ridge, Lasso, and Elastic-Net), to predict Medicare claim costs of Type 2 diabetes patients with other diagnoses. We used Data from Entrepreneur’s Medicare Claims Synthetic Public Use Files (DE-SynPUFs) for our analysis.

Built a car price prediction from Kaggle dataset solution using Linear Regression and also Lasso Regression

Project 2 Group C - Predicting FinTech Bootcamp Graduate Salaries

Repository consisting of the notebooks I worked on to submit my courseworks at Royal Holloway

My solution to House-Prices Advanced Regression Techniques, A beginner-friendly project on Kaggle.

Regresión Lineal Múltiple con Modelos Regularizados (Lasso y Ridge) y Sin Regularizar

NYU CSCI-GA 3033 Final Project

Prime video view time exploration and prediction

Practical Implementation of Linear Regression on Boston Housing Price Prediction

Practical Implementation of Linear Regression on Algerian Forest Fire Dataset.

Genetic assignment of individuals to known source populations using network estimation tools.

Using the mtcars dataset, I'm exploring three different types of regression: (1) Lasso; (2) Ridge ; (3) StepLR . I'm providing my recommendations on which one is the most ideal.

Building Advanced regression models (Lasso and Ridge) for house price prediction in the Australian market