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 – predictions (Batch Prediction)

Batch prediction is used when you don’t require an immediate response and want to get predictions from the accumulated data via a single request. Follow these steps to perform batch prediction for the models we trained earlier:

  1. Go to Models from the left menu of the console.
  2. Click on the model you want to work with.
  3. Click on the version of the model you want to work with.
  4. From the top menu, click on BATCH PREDICT.
  5. Click on the blue CREATE BATCH PREDICTION button:

After clicking on CREATE BATCH PREDICTION, you need to define some parameters, such as the batch prediction’s name, source, output, and so on. Let’s analyze each of them:

  • Batch prediction name: Enter a name for the batch prediction.
  • Select source: Here, you need to specify the source of the value that will be used in batch prediction. You can source either the BigQuery table or the file...