Let's start with Chapter 1, The Python Machine Learning Ecosystem.
In the first chapter, we began with an overview of ML with Python. We started with the ML workflow, which included acquisition, inspection, preparation, modeling evaluation, and deployment. Then we studied the various Python libraries and functions that are needed for each step of the workflow. Lastly, we set up our ML environment to execute the projects.
Chapter 2, Building an App to Find Underpriced Apartments, as the name says, was based on building an app to find underpriced apartments. Initially, we listed our data to find the source of the apartments in the required location. Then, we inspected the data, and after preparing and visualizing the data, we performed regression modeling. Linear regression is a type of supervised ML. Supervised, in this context, simply means we provide...
