Official Google Cloud Certified Professional Machine Learning Engineer Study Guide (Sybex Study Guide)

This is a written a well organized, comprehensive guide that includes features that make studying more efficient, including review questions, exam essentials summary sections, practice tests, a lot of insights about when and when not to use services for different use cases.The book provides an overview of general ML concepts engineers need to understand, like feature engineering, data leakage, hyperparameter optimization, and evaluation methods. There are also descriptions of important statistic topics without a lot of extra details you might find in a math text but don't need to know for the exam. The links to additional learning material are especially helpful for getting more explanation and details on ML concepts.In addition to the necessary ML background you need for the exam, the book has detailed information about how to use Google Cloud ML services. Some of that material is at a high level, like how to create a model in BigQuery ML, and some of it is down in the weeds optimization details, like suggestions to use the tf.data.Dataset.prefetch function in TensorfFlow to overlap preprocessing and model execution of a training step. There are multiple chapters that dive into the engineering aspects of ML covering model building, security, scaling, and monitoring.I'll definitely be using this study guide when I recertify.

This book was my primary source of preparation for the Google PMLE Certification and was apt. Earlier I went over content in cloud skills boost, did the labs and they were great. However the unique thing about this book is - it covers all and keeps you focused to what is required for the exam. Thanks to the Mona Mona and Ramamurthy to have taken the effort and time to write this both with high quality.

In the Log Scaling section at page 26 the authors wrote "log of (100,000) = 100 and log of (100) = 10", which doesn't make sense. There is no indication that the mathematical Logarithm function requires a base to have a meaning (e.g. 2, e, 10). And even assuming the base is 10, Log base 10 of (100,000) = 5 (not 100) and Log base 10 of (100) = 2 (not 10).You would expect the content of an Official Google Cloud ML certification study guide to be accurate, high-quality and vetted by some Google Cloud experts/authority. That's not the case for this book!What makes this guide official when basic mistakes are found and content is poorly written?A guide about Machine Learning requires at a minimum coverage of basic statistical terms, e.g. mean, median, mode, standard deviation, etc. Not only these are NOT covered at all, but some math is simply wrong.Last, there are very few examples to assist the reader in understanding complex concepts, e.g. Convolutional Neural Networks, and not much code is shared, which for Data Preparation should be a must.

The book is really focused on helping you pass the PMLE test. It contains just the right amount of information - no more, no less, so you can optimize your use of time. The questions at the end of each chapter are very helpful for that purpose and the 2 bonus exams are quite realistic. Overall an excellent investment.

I bought this book in July '24. I recently learned that Google released a new exam guide effective Oct 1st, 2024. A few things that got added relate to implementing RAG applications by using Vertex AI agent building, ingesting different data sources into Vertex AI for inference, Leveraging a variety of foundational and open-source models in Model Garden, Evaluating generative AI solutions, and Fine-tuning foundational models (e.g., Vertex AI, Model Generation).Does the Author have any plans to update the book?

I found this book to be an invaluable resource in preparing for the GCP ML certification exam. The content aligns seamlessly with the latest exam curriculum, making it an effective study companion. The comprehensive coverage of Google Cloud Vertex AI and BigQuery ML contributed significantly to my understanding of these topics. Overall, a highly recommended guide for anyone gearing up for the exam.

The book covers both the old gcp syllabus for ML engineer and the new exam syllabus.First three chapters focus on the basics.Chapter 4 onwards is on google cloud ML concepts. It also has 240 questions which provides lots of practice for the exam.

This book is a great resource for studying for GCP machine learning certification. The review questions were very useful. Highly recommend this book if you're planning to get this certification.