To get the most out of this book
You will need a basic working knowledge of Kubernetes and Python to get the most out of this book's technical exercises. The platform uses multiple software components to cover the full ML development life cycle. You will need the recommended hardware to run all the components with ease.
Running the platform requires a good amount of compute resources. If you do not have the required number of CPU cores and memory on your desktop or laptop computer, we recommend running a virtual machine on Google Cloud or any other cloud platform.
If you are using the digital version of this book, we advise you to type the code yourself or access the code from the book's GitHub repository (a link is available in the next section). Doing so will help you avoid any potential errors related to the copying and pasting of code.
A good follow-up after you finish with this book is to create a proof of concept within your team or organization using the platform. Assess the benefits and learn how you can further optimize your organization's data science and ML project life cycle.