This repository contains my practice notebooks from reading Hands-On Machine Learning by Auerelien Geron. It's an amazing book which I highly recommend to anyone, especially if you are having trouble connecting theory to application.
The second chapter alone has really helped put the different parts of a data science project into perspective. From developing a target to deploying and monitoring a model in the first 100 pages, it's already answered many of my questions.
Note: While the code and visualizations may seem familiar, please pay more attention to the notes and comments while skimming the content. I hope they can help add immediate value to you in some way.
