No-Code Machine Learning Using Amazon AWS SageMaker Canvas

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No-Code Machine Learning Using Amazon AWS SageMaker Canvas

Coursera · Beginner ·☁️ DevOps & Cloud ·3mo ago
Skills: ML Pipelines80%

Key Takeaways

Builds no-code machine learning models using Amazon AWS SageMaker Canvas

Original Description

This course features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. In this course, you'll gain hands-on experience with AWS SageMaker Canvas, a powerful no-code tool for machine learning. You'll start by understanding the basics of machine learning and Amazon Web Services (AWS), laying a solid foundation for the rest of the course. As you progress, you'll explore how SageMaker Canvas simplifies building, training, and deploying machine learning models with no coding required. Throughout the course, you'll complete four projects that cover real-world applications such as banknote authentication, spam SMS detection, customer churn prediction, and wine quality prediction. These projects will guide you through adding training data, building models, making predictions, and validating accuracy. The hands-on experience will deepen your understanding and help you master SageMaker Canvas' interface and capabilities. By the end of the course, you'll be able to apply your skills to a variety of machine learning tasks using SageMaker Canvas. This course is ideal for individuals who are new to machine learning or those looking to streamline the process of building machine learning models without writing code.
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