The Definitive Guide to Google Vertex AI
Accelerate your machine learning journey with Google Cloud Vertex AI and MLOps best practices
Created by Jasmeet Bhatia, Kartik Chaudhary
Explore how to streamline machine learning projects using Google Vertex AI and MLOps best practices. Gain practical experience building, deploying, and managing real-world AI solutions on Google Cloud. Move beyond theory and get hands-on with the tools that power production-grade ML workflows.
Packt | Dec 2023 | 422 min
What You Will Learn
You will work through practical exercises that guide you from setting up data and experiments to deploying models using Google Vertex AI. By applying tools for computer vision, natural language processing, and generative AI, you will learn to integrate pre-built solutions and customize workflows for real-world use cases. Each step builds your confidence in managing end-to-end ML projects.
Key Features
- Build and deploy ML models using Vision, NLP, and recommendation systems
- Manage data, experiments, and workflows with Vertex AI's integrated MLOps tools
- Leverage no-code, low-code, and custom AI solutions for faster project delivery
Target Audience
This content is ideal for machine learning practitioners, data scientists, and engineers with some experience in ML who want to master end-to-end solution development on Google Cloud. If your goal is to implement production-ready AI workflows using MLOps best practices, you will find actionable guidance and tools to accelerate your projects.
