Overview

In this unit, we learnt how to apply the fundamentals of linear regression in Scikit-Learn. The unit also aimed to show how to model linear relationships between a single independent and dependent variable, and multiple independent variables and a single dependent variable.

My Reflection

This unit zoomed in further on linear regression and its implementation with Python's Sickit-Learn. Overall, regression is a method of supervised machine learning that allows the prediction of a target with continuous numerical type of data, helping to uncover patterns, trends, and dependencies in data, which is essential for tasks such as forecasting, risk assessment, and decision-making. It was one of the most applicable methods for our team project, which is mainly about analysing and generating insights from Airbnb 2019 dataset.

This was a light week that allowed us to focus more on the team project. For the team project, we started distributing our roles in the assignment. We split the assignment's roles to two overall groups. The first is related to code writing for analysis, model building and evaluation. the second is related to report writing of the different sections. I handled writing and running the initial code for the regression model, to predict prices, based on , in addition to the final editing and proofreading of the report.