Packt
No-Code Machine Learning Using Amazon AWS SageMaker Canvas
Packt

No-Code Machine Learning Using Amazon AWS SageMaker Canvas

Gain insight into a topic and learn the fundamentals.
Beginner level

Recommended experience

3 hours to complete
3 weeks at 1 hour a week
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
Beginner level

Recommended experience

3 hours to complete
3 weeks at 1 hour a week
Flexible schedule
Learn at your own pace

What you'll learn

  • Understand machine learning basics and AWS SageMaker Canvas, including data setup and environment prep.

  • Apply ML techniques to build, train, and test models on real-world datasets in a no-code platform.

  • Analyze and interpret model predictions to validate accuracy and improve performance.

  • Create no-code machine learning solutions to solve business problems using AWS SageMaker Canvas.

Details to know

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Recently updated!

October 2024

Assessments

5 assignments

Taught in English

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There are 12 modules in this course

In this module, we will introduce the basics of machine learning, covering fundamental concepts and applications. You will gain an understanding of what machine learning is and how it works, setting the foundation for the rest of the course.

What's included

2 videos1 reading

In this module, we will explore Amazon Web Services (AWS), the platform that powers SageMaker Canvas. You’ll learn what AWS is, its key services, and how to sign in to the AWS console for cloud-based machine learning activities.

What's included

2 videos

In this module, we will dive into Amazon SageMaker, a powerful tool for building and training machine learning models. You’ll also get introduced to SageMaker Canvas, the no-code interface that enables you to create models without needing programming skills.

What's included

2 videos

In this module, we will walk through setting up your SageMaker domain and user environment. Additionally, you'll learn how to configure data in S3 Buckets, ensuring everything is ready for building machine learning models in SageMaker.

What's included

2 videos1 assignment

In this module, we will explore the SageMaker Canvas interface, guiding you through its various features and functionalities. This walkthrough will help you efficiently navigate and use SageMaker Canvas for machine learning tasks.

What's included

1 video

In this module, we will apply what we've learned to build a model for banknote authentication. You'll gather training data, build a predictive model, and validate its performance through batch prediction and accuracy testing.

What's included

4 videos

In this module, we will focus on detecting spam SMS messages using machine learning. You’ll learn how to prepare your data, build a model, and evaluate its predictions to ensure it accurately detects spam.

What's included

3 videos1 assignment

In this module, we will predict customer churn using machine learning. You'll import relevant customer data, build a predictive model, and assess its ability to forecast churn rates accurately.

What's included

3 videos

In this module, we will create a model to predict wine quality. You will work with datasets, build a model, and test its performance, learning how to combine multiple data sources for better results.

What's included

3 videos1 assignment

In this module, you will complete an assignment where you predict white wine quality. This hands-on exercise will reinforce your learning and improve your ability to apply machine learning techniques using SageMaker Canvas.

What's included

1 video

In this module, we will cover the versioning feature in SageMaker Canvas. You'll learn how to manage different versions of your models, ensuring you can track changes and improvements over time.

What's included

1 video1 assignment

In this module, we will conclude the course with tips on obtaining more datasets, getting help with SageMaker Canvas, and congratulating you on completing the course. You'll also receive guidance on your next steps in mastering no-code machine learning.

What's included

3 videos1 assignment

Instructor

Packt - Course Instructors
Packt
372 Courses9,744 learners

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