AWS re:Post Live | Bridging No-Code and Code-First Machine Learning Environments - Live on September 9th!

Note: This episode aired on September 9th. You can watch the recording on demand by clicking here or on the image below.

Welcome to our Community Article for the upcoming AWS re:Post Live show scheduled for Monday, September 9th at 11 am PST / 2 pm EST on twitch.tv/aws! On this episode, join Principal Solutions Architect Anup Sivadas, Principal Technical Account Manager Rajakumar Sampathkumar, and Sr. Solutions Architect of AI/ML Meena Thandavarayan as they discuss Bridging No-Code and Code-First Machine Learning Environments with you, our AWS re:Post community, and answer your most burning questions on AWS SageMaker, AI, Machine Learning, LLMs, and more! If you have any questions please add them in the comments section at the bottom of this article and we will answer them as part of our live show on Monday, September 9th over on Twitch. If your question is selected you will be awarded 5 re:Post points!

Amazon SageMaker Canvas is a powerful no-code ML tool designed for business and data teams to generate accurate predictions without writing code or having extensive ML experience. With its intuitive visual interface, SageMaker Canvas simplifies the process of loading, cleansing, and transforming datasets, and building ML models, making it accessible to a broader audience. However, as your ML needs evolve, or if you require more advanced customization and control, you may want to transition from a no-code environment to a code-first approach. This is where the seamless integration between SageMaker Canvas and SageMaker Studio comes into play! Join us on this episode to find out more!