Building AI Powered Applications with ML APIs & Amazon SageMaker


Details
Amazon SageMaker provides every developer and data scientist with the ability to build, train, and deploy machine learning models quickly. Amazon SageMaker is a fully-managed service that covers the entire machine learning workflow to label and prepare your data, choose an algorithm, train the algorithm, tune and optimize it for deployment, make predictions, and take action.
Your models get to production faster with much less effort and lower cost.
In this workshop, Randall Hunt, Senior Technical Evangelist and Software Engineer at Amazon Web Services will walk you through the various capabilities and features in the AWS Machine Learning portfolio:
- Rekognition
- Comprehend
- Translate
- Transcribe
- And more!
Next we’ll dive into a LIVE CODING EXERCISE and workshop with Amazon SageMaker where we’ll train an object detection network with Amazon SageMaker.
ABOUT THE PRSENTER
Randall Hunt is a Senior Technical Evangelist and Software Engineer at Amazon Web Services in Los Angeles. Based on his experiences at SpaceX, MongoDB, AWS, and NASA, Randall has dealt with a wide range of both business and technical issues across many different verticals.
As a Sr. Technical Evangelist, Randall often speaks at conferences and events across the world where he helps developers maximize their productivity in the cloud. He's particularly interested in databases, serverless, and DevOps. He holds all seven AWS certifications.

Building AI Powered Applications with ML APIs & Amazon SageMaker