Journey to Become a Google Cloud Machine Learning Engineer
This is a guide to learning and mastering machine learning in Google Cloud and a roadmap to becoming a Google Cloud certified Machine Learning Engineer. The book emphasizes developing the “mind and hand” to build a broad and strong knowledge base, develop hands-on skills, and get certified as a Google Cloud Machine Learning Engineer.
Offered by
Difficulty Level
Intermediate
Completion Time
11h
Language
English
About Book
Who Is This Book For?
Anyone from the cloud computing, data analytics, and machine learning domains, such as cloud engineers, data scientists, data engineers, ML practitioners, and engineers, will be able to acquire the knowledge and skills and achieve the Google Cloud professional ML Engineer certification with this study guide. Basic knowledge of Google Cloud Platform and Python programming is required to get the most out of this book.
Journey to Become a Google Cloud Machine Learning Engineer
- About Book
- Who Is This Book For?
- Book Content
Book content
chapters • 11h total length
Comprehending Google Cloud Services
Mastering Python Programming
Preparing for ML Development
Developing and Deploying ML Models
Understanding Neural Networks and Deep Learning
Learning BQ/BQML, TensorFlow and Keras
Exploring Google Cloud Vertex AI
Discovering Google Cloud ML API
Using Google Cloud ML Best Practices
Achieving the GCP ML Certification
Appendix 1 - Practicing with Basic GCP Services
Appendix 2 - Practicing with Python Data Library
Appendix 3 - Practicing with ScikitLearn
Appendix 4 - Practicing with Vertex AI
Appendix 5 - Practicing with Google Cloud ML API
Related Resources
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