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

Vertex AI Training

In an ML model development process, training jobs are discrete tasks that generate ML models. In Vertex AI, you can choose different training methods based on the source of model and data; Vertex AI AutoML, which is managed by Google, uses Google’s model and your data to train, and the Vertex AI platform, with user-defined code or custom containers, utilizes your model and your data to perform model training.

Vertex AI AutoML

Vertex AI AutoML is a managed Google Cloud service that enables users to build models across a wide variety of use cases without writing any code. The objective is to enable ML model development for various levels of AI expertise.

The types of models supported by Vertex AutoML are shown in Table 7.1:

Table 7.1 – Vertex AI AutoML models

When creating an AutoML training pipeline job, you have the following options:

  • Dataset: Managed by Vertex AI and uploaded by a user
  • Model type: Selected...