Syracuse University, Masters of Applied Data Science -SCM 651 Business Analytics

A simple implementation of univariate linear regression using gradient descent, built with NumPy and Matplotlib.

Implementing the gradient descent algorithm from scratch to perform univariate linear regression to analyze the profit made by a bike sharing company.

Code for a basic univariate linear regression model using scikit-learn

Linear Regression is implemented to identify the relationship between the profit of a bakery and the population of different cities. The main objective is to find the next city in which a new outlet should be opened.

🤖 Implement linear regression from scratch in Python using NumPy to grasp its fundamentals, including cost function and gradient descent training.

In this notebook, we want to create a machine learning model from scratch to predict car prices using independent variables.

Create a simple, univariate linear regression model that predicts the salary from a person's experience (measured in years), using the gradiant descent algorithm.