/python_linearregression

Linear Regression of Uber and Lyft ride-hailing data

Primary LanguageJupyter NotebookMIT LicenseMIT

image info

SARChI - Python: Linear Regression

South Africa-Switzerland Bilateral Research Chair in Blockchain Technology aims to explore blockchain integrations with real-world applications and development in Agric-food.

Context

As a research center, our focus is more than just blockchain technology, but we have expertise in web development, data analysis, data science, and machine learning development. In this repository, look at a popular algorithm used in machine learning solutions, regression. We introduce linear regression and the mathematics behind the algorithm. We use the fundamental gained from our Machine Learning with Python, and apply linear regression to determine the price of an Uber/Lyft trip.

Dataset

The dataset used for the linear regression demonstration is Uber & Lyft Cab Prices.

Methods

In the notebook, we analyse Uber and Lyft ride-hailing data from Boston, United States of America. Prices of ride hailing services fluctuate regularly due to factors such like demand-bursts or availability constraints, therefore we dive into the dataset to uncover relationships that influence the price of a trip.

Resources