Build a regularized regression model to predict the price of houses with the available independent variables

Implementation of Machine Learning algorithms using MatLab.

Built a regression model to predict bike demand on data from Seoul, South Korea. and employed one hot encoding to create dummy variables Benchmarked Cat Boost against Linear regression, Lasso and Ridge regression, Gradient Boost and performed feature engineering and tuned the hyperparameters for the optimum performance

Machine Learning by Stanford University at Coursera

In this project I tried to implement linear regression and regularized linear regression by my own and compare performance to sklearn model.

High dimensional linear regression with missing via adaptive SLOPE

The course studies fundamentals of distributed machine learning algorithms and the fundamentals of deep learning. We will cover the basics of machine learning and introduce techniques and systems that enable machine learning algorithms to be efficiently parallelized.

Implementation of Linear Ridge regression and Regularized logistic regression

Predict the vehicle price from the open source Auto data set using linear regression. In this data set, we have prices for 205 automobiles, along with other features such as fuel type, engine type,engine size,etc.

This are my solutions to the course Machine Learning from Coursera by Prof. Andrew Ng

In linear regression, regularization is a process of making the model more regular or simpler by shrinking the model coefficient to be closer to zero or absolute, ultimately to address over fitting.

Regularization, PCA and Linear Regression are implemented.

Assessing Beijing’s PM 2.5 pollution: severity, weather impact in R

Competition: https://www.kaggle.com/c/house-prices-advanced-regression-techniques

Advanced Regression Predict_ House Prices

High Throughput Light Weight Regularized Regression Modeling for Molecular Data

Regularized regression using a forest fire data set

Implementation of Ridge Regression Algorithm (Regularised Linear Regression)

Advanced regression model to predict housing price for an use case in Australia.