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

Google Cloud Sight API

The Google Cloud Sight API offer powerful Google pre-trained machine learning models for vision processing and video processing. We will examine the concepts for both the Cloud Vision API and the Cloud Video API.

The Cloud Vision API

The Cloud Vision API is a tool to decipher images through Google’s pre-trained advanced ML models. It can interpret images and classify them into lots of categories. It can extract and detect text, whether the text is within pictures or document photos.

Google Cloud Vision allows developers to easily integrate vision detection features within applications, including image labeling, landmark detection, logo detection, and content detection:

  • Image label detection can detect, identify, and label objects, locations, activities, animal species, products, and many other things that exist within an image.
  • Landmark detection can identify landmarks, such as popular landmarks and natural or man-made structures,...