Multiple Regression Analysis

Used Machine Learning algorithms to make various types of predictions.

Basics of Machine Learning

The linear regression models are developed as part of final report of "Advanced Analytics" module at University of Derby.

The MATLAB code analyses stock prices of a company and predicts the closing price. The algorithms implemented for predicting closing price are: (a)Kalman Filter (b)Kalman Multiple Linear Regression The algorithms implemented for analysing the trends in a stock (c) Bollinger bands (d). Chaikin Oscillator Output - 1. Graphs showing the predicted a…

Ames Housing Prices: Advanced Regression Techniques

Linear Regression and polynomial regression using Python

Repo for multiple regression assignments in Quant III for EDUC467.

This repository contains all the Machine Learning projects that I have developed/worked in the areas of Natural Language Processing and Computer Vision by using the Machine Learning frameworks such as scikit-learn and h2o.

Built house price prediction model by using linear regression and k nearest neighbors algorithm. Applied machine learning techniques like ridge, lasso, and gradient descent for optimization in Python

Multiple Linear Regression with TensorFlow

Pythonで単回帰分析と重回帰分析、ディープラーニングで回帰と分類

Learn about Feature Engineering and get familiar with Advanced regression techniques like Lasso, ElasticNet, Gradient Boosting, etc.

A simple multiple regression on two datasets (lm and closed form solution)

R script that performs complete multiple regression on two data sets

Conducted multivariate data analysis and exploration of wine quality dataset, and built predictive models using multiple regression in R