Are you looking to make better business decisions using machine learning (ML) without writing code or requiring ML experience? Amazon SageMaker Canvas enables business analysts to achieve effective business outcomes with a visual point-and-click interface allowing them to understand their data better and generate accurate ML predictions without writing a single line of code. Join us for an AWS Online Tech Talk to learn how you can use Amazon SageMaker Canvas to quickly and easily build ML models, analyze models, and generate accurate predictions with just a few clicks.
Learning Objectives:
* Objective 1: Learn how you can use SageMaker Canvas to make better business decisions using ML, without writing code.
* Objective 2: Learn how you can use SageMaker Canvas to address your business problems, such as sales forecasting.
* Objective 3: Find out how you can share models and datasets with data scientists so they can validate and further refine ML models.
***To learn more about the services featured in this talk, please visit: https://aws.amazon.com/sagemaker/canvas Subscribe to AWS Online Tech Talks On AWS:
https://www.youtube.com/@AWSOnlineTechTalks?sub_confirmation=1
Follow Amazon Web Services:
Official Website: https://aws.amazon.com/what-is-aws
Twitch: https://twitch.tv/aws
Twitter: https://twitter.com/awsdevelopers
Facebook: https://facebook.com/amazonwebservices
Instagram: https://instagram.com/amazonwebservices
☁️ AWS Online Tech Talks cover a wide range of topics and expertise levels through technical deep dives, demos, customer examples, and live Q&A with AWS experts. Builders can choose from bite-sized 15-minute sessions, insightful fireside chats, immersive virtual workshops, interactive office hours, or watch on-demand tech talks at your own pace. Join us to fuel your learning journey with AWS.
#AWS
Learning Objectives:
* Objective 1: Learn how you can use SageMaker Canvas to make better business decisions using ML, without writing code.
* Objective 2: Learn how you can use SageMaker Canvas to address your business problems, such as sales forecasting.
* Objective 3: Find out how you can share models and datasets with data scientists so they can validate and further refine ML models.
***To learn more about the services featured in this talk, please visit: https://aws.amazon.com/sagemaker/canvas Subscribe to AWS Online Tech Talks On AWS:
https://www.youtube.com/@AWSOnlineTechTalks?sub_confirmation=1
Follow Amazon Web Services:
Official Website: https://aws.amazon.com/what-is-aws
Twitch: https://twitch.tv/aws
Twitter: https://twitter.com/awsdevelopers
Facebook: https://facebook.com/amazonwebservices
Instagram: https://instagram.com/amazonwebservices
☁️ AWS Online Tech Talks cover a wide range of topics and expertise levels through technical deep dives, demos, customer examples, and live Q&A with AWS experts. Builders can choose from bite-sized 15-minute sessions, insightful fireside chats, immersive virtual workshops, interactive office hours, or watch on-demand tech talks at your own pace. Join us to fuel your learning journey with AWS.
#AWS
- Category
- AWS Developers
- Tags
- machine learning, ml, no code

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