Book Image

Journey to Become a Google Cloud Machine Learning Engineer

By : Dr. Logan Song
Book Image

Journey to Become a Google Cloud Machine Learning Engineer

By: Dr. Logan Song

Overview of this book

This book aims to provide a study guide to learn and master machine learning in Google Cloud: to build a broad and strong knowledge base, train hands-on skills, and get certified as a Google Cloud Machine Learning Engineer. The book is for someone who has the basic Google Cloud Platform (GCP) knowledge and skills, and basic Python programming skills, and wants to learn machine learning in GCP to take their next step toward becoming a Google Cloud Certified Machine Learning professional. The book starts by laying the foundations of Google Cloud Platform and Python programming, followed the by building blocks of machine learning, then focusing on machine learning in Google Cloud, and finally ends the studying for the Google Cloud Machine Learning certification by integrating all the knowledge and skills together. The book is based on the graduate courses the author has been teaching at the University of Texas at Dallas. When going through the chapters, the reader is expected to study the concepts, complete the exercises, understand and practice the labs in the appendices, and study each exam question thoroughly. Then, at the end of the learning journey, you can expect to harvest the knowledge, skills, and a certificate.
Table of Contents (23 chapters)
1
Part 1: Starting with GCP and Python
4
Part 2: Introducing Machine Learning
8
Part 3: Mastering ML in GCP
13
Part 4: Accomplishing GCP ML Certification
15
Part 5: Appendices
Appendix 2: Practicing Using the Python Data Libraries

Appendix 1: Practicing with Basic GCP Services

In this appendix, we will show some GCP resource provisioning examples, using the Google Cloud console and Cloud Shell. We will use the following architecture to practice using the Google Cloud console, as shown in Figure 11.1:

  • A VPC network, VPC1, and two subnets in it: a public subnet1 and a private subnet2
  • A virtual machine (VM) in the public subnet1 that has an external IP address and can be accessed from the internet
  • A VM in the private subnet2 that does not have an external IP address and thus can only be accessed from the console browser, or from VMs within the same VPC
  • Another VPC network, VPC2, and one subnet within VPC2: a private subnet8
  • A VM in the private subnet8
  • Peering between VPC1 and VPC2

Figure 11.1 – A sample architecture for GCP console practice

In the GCP practice diagram in Figure 11.1, public subnet1 is accessible from the internet. There is a Google...