End To End Machine Learning Project

This article presents a comprehensive guide to executing an end-to-end machine learning project. It covers every step of the process, from initial data acquisition to model deployment.

The guide starts with acquiring and loading data, utilizing Python libraries such as pandas, urllib, and pathlib. It then delves into preliminary data analysis, including visualizing and understanding data structure and distributions.

The article also explores preprocessing techniques, such as handling text and categorical attributes and feature scaling,…