Build, Train, and Deploy ML Models with Keras on Google Cloud explores the end-to-end workflow for developing machine learning models with TensorFlow, Keras, and Vertax AI.
Designed for professional building machine learning (ML) solutions in Google Cloud, this course will teach you how to prepare data, create machine learning models, and move them into production environments. You’ll work with TensorFlow tools and Keras APIs while examining different approaches to model development and deployment.
This course explores the key fundamentals of ML workflows, including:
- Preparing and processing large datasets for machine learning tasks
- Building machine learning models with TensorFlow and Keras tools
- Comparing approaches for creating simple and advanced model architectures
- Deploying and scaling ML models in production environments with Vertex AI
You’ll learn how data pipelines support model training workflows, and different strategies for supporting deployment at scale in Google Cloud environments.
By the end of this course, you’ll be able to develop ML workflows, create and deploy ML models, and support scalable ML operations using Google Cloud tools and services.
