Google Cloud AutoML ( googlecloudautoml | 7 hours )

• Basic knowledge of data analytics
• Familiarity with machine learning

Audience

• Data scientists
• Data analysts
• Developers

Google Cloud AutoML is a machine learning (ML) platform that enables users to build, train, and deploy customized ML models specific to their business needs.

This instructor-led, live training (online or onsite) is aimed at data scientists, data analysts, and developers who wish to explore AutoML products and features to create and deploy custom ML training models with minimal effort.

By the end of this training, participants will be able to:

• Explore the AutoML product line to implement different services for various data types.
• Prepare and label datasets to create custom ML models.
• Train and manage models to produce accurate and fair machine learning models.
• Make predictions using trained models to meet business objectives and needs.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

Introduction

Overview of AutoML Features and Architecture

• Google’s ML ecosystem
• AutoML line of products

Working With Google’s Machine Learning Ecosystem

• Applications for AutoML products
• Challenges and limitations

Evaluating Content Using AutoML Natural Language

• Preparing datasets
• Creating and deploying models
• Text and document training (classification, extraction, analysis)

Classifying Images Using AutoML Vision

• Labeling images
• Training and evaluating models
• AutoML Vision Edge

Creating Translation Models Using AutoML Translation

• Preparing datasets (source and target language)
• Creating and managing models
• Testing models

Making Predictions from Trained Models

• Analyzing documents
• Image prediction
• Translating content

Exploring Other AutoML Products

• AutoML Tables for structured data
• AutoML Video Intelligence for videos

Troubleshooting

Summary and Conclusion