Journey to Become a Google Cloud Machine Learning Engineer
Build the mind and hand of a Google Certified ML professional
1st Edition
Published on 3. June 2024
330 pages
978-1-80323-941-5 (ISBN)
Description
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Person
Song Dr. Logan :
Dr. Logan Song is the enterprise cloud director and chief cloud architect at Dito. With 25+ years of professional experience, Dr. Song is highly skilled in enterprise information technologies, specializing in cloud computing and machine learning. He is a Google Cloud-certified professional solution architect and machine learning engineer, an AWS-certified professional solution architect and machine learning specialist, and a Microsoft-certified Azure solution architect expert. Dr. Song holds a Ph.D. in industrial engineering, an MS in computer science, and an ME in management engineering. Currently, he is also an adjunct professor at the University of Texas at Dallas, teaching cloud computing and machine learning courses.
Dr. Logan Song is the enterprise cloud director and chief cloud architect at Dito. With 25+ years of professional experience, Dr. Song is highly skilled in enterprise information technologies, specializing in cloud computing and machine learning. He is a Google Cloud-certified professional solution architect and machine learning engineer, an AWS-certified professional solution architect and machine learning specialist, and a Microsoft-certified Azure solution architect expert. Dr. Song holds a Ph.D. in industrial engineering, an MS in computer science, and an ME in management engineering. Currently, he is also an adjunct professor at the University of Texas at Dallas, teaching cloud computing and machine learning courses.
Content
Table of Contents - 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
- 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
