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

Project 2 Group C - Predicting FinTech Bootcamp Graduate Salaries

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

It was a competition on KAGGLE for prediction on the most sales products on bikes via their features

House Price Prediction can help the customer to arrange the right time to Purchase a House. It is An - ML based Approach which Predicts the Estimated Price of Housing in Mumbai City.

Predicting house price

Regression Machine Learning Project

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

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 Gradient Boosting model by employing Lasso Regularization and Hyper-parameter tuning

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

Metis project 2/7

"Learning R for data scientists." This phrase describes the process of acquiring the skills and knowledge necessary to use the R programming language for data analysis.

NYU CSCI-GA 3033 Final Project

Practical Implementation of Linear Regression on Boston Housing Price Prediction

Advanced Regression model on Housing Data from Australia for my Upgrad - IIITB AI ML PG Course

A series of Statistical Modelling assignments with the use of R. Applications of Linear, Polynomial, Logistic and Poisson Regression in various datasets

Repository about the projects in the course of Modeling and control of cyberphysical systems at PoliTo in 2022/2023

ML | Regression Analysis| Random Forest| XGBoost| Gradient Boost| EDA| Feature Engineering| Feature selection

Analysis and Modelling data from King county housing data