Gemstone Price Prediction - End to End ML Project with AWS deployment

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

Sub-seasonal temperature and heatwave prediction in Central Europe with AI (linear and random forest machine learning models)

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.

Metis project 2/7

This is First Project of Machine Learning by me

In this series of notebooks, we will dive into each step of the data analysis process of a data set with some information about a list of cars and several attibutes, including their prices. So essentially we will develop a model to predict cars price.

A small project addressing a regression problem explains implementation of multiple linear regression techniques, hyperparameter tuning, collinearity, model overfitting and complexity using LASSO, Ridge and Elastic net

Model Building and Testing using Ridge, Lasso and ElasticNet Methods

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

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

Practical Implementation of Linear Regression on Boston Housing Price Prediction

Forest Fire Data

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.

In this project we are predicting the closing price of stocks by regression models

Practical Implementation of Linear Regression on Algerian Forest Fire Dataset.

End-to-end machine learning regression model for predicting housing prices in Bengaluru, with Heroku deployment.

Using OLS regression (and Ridge and Lasso to compare), we worked on a project that uses a dataset to predict housing prices based on user inputs on house details.

School exercise - Multivariate Statistical Methods subject