Do’s, Don’ts, and Gotchas from working with AI Models using Amazon SageMaker

This month we're pleased to have Brian Hough return to talk about SageMaker. At always we'll start socializing at 5:30 PM and then the main talk with start at the top of the hour (approximately).

This talk will focus on my exploration and learnings of what goes into constructing MLOps pipelines, from conducting data analysis to running generative AI models.

This past year’s deep dive into AI has unveiled a universe far more expansive than I could have imagined. Throughout this talk, I will share what I’ve learned so far, demonstrating how you can get started with various models, train your own datasets, and deploy your own AI models to address numerous use-case.

From setting up your own SageMaker domain to an endpoint for your hyperparemeter-tuned model, I will walk you through the lessons I’ve learned to accelerate your journey into AI or elevate your understanding of the possibilities that building in the cloud presents, thanks to platforms like Amazon SageMaker.

Regardless of your prior experience in AI, I look forward to sharing an insightful look behind the AI curtain and present the practicalities of running AI models, while demystifying the complex world of machine learning operations, on AWS