No detailed description available for "Journey to Become a Google Cloud Machine Learning Engineer".
Sprache
Verlagsort
Basel/Berlin/Boston
Großbritannien
Zielgruppe
Editions-Typ
Produkt-Hinweis
Dateigröße
ISBN-13
978-1-80323-941-5 (9781803239415)
Schweitzer Klassifikation
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.
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
