Machine Learning with Amazon SageMaker is a hands-on workshop designed to provide data scientists and developers with end-to-end understanding of the Amazon SageMaker platform, from handling data and features, to building, training, tuning, and deploying ML models. The workshop consists of theoretical modules and hands-on labs that focus on data quality, feature engineering, SageMaker built-in algorithms, and advanced concepts like model deployment on XGBoost.
Agenda (Pacific Time):
* 9:00 AM - 9:15 AM: Welcome & Introductions
* 9:15 AM - 10:15 AM: Session: "Introduction to Amazon SageMaker and Data for Machine Learning"
* 10:15 AM - 11:00 AM: Lab: "Feature Engineering with Amazon SageMaker"
* 11:00 AM - 11:15 AM: Break
* 11:15 AM - 12:15 AM: Session: "Create Model, Prediction and Inference with Amazon SageMaker"
* 12:15 PM - 12:45 PM: Lunch
* 12:45 PM - 1:15 PM: Lab: "Train, Tune and Deploy Model using Amazon SageMaker Built-in Algorithm"
* 1:15 PM - 1:30 PM: Wrap-up / Q&A
* Learn how to build, train, tune, and deploy ML models with Amazon SageMaker in production-like scenarios
* Explore best practices for using Amazon SageMaker’s built-in algorithms in ML production systems
* Learn AWS services for managing data, features, ML models, and projects through hands-on experience
* Address your questions about doing ML in the cloud to experts from AWS and Provectus
Who Should Attend
Data Scientists, ML Engineers, MLOps and QA professionals, and developers. Basic familiarity with AWS is recommended.
Chaitra Mathur (AWS)
Sr Solutions Architect at AWS. Chaitra is a Sr Solutions Architect at AWS, focused on accelerating customer’s cloud adoption journey. In her career she has been Technology Lead at leading consulting firms, driving large scale design and delivery of digital experience solutions to customers. She is AWS Machine Learning certified and enjoys solving Machine Learning problems for customers using AWS services.
Sr ML Engineer at Provectus. As a technology leader, Rinat has been helping IT organizations in various industries to design, build, implement, and operate large-scale AI/ML solutions, covering all aspects from data and infrastructure for ML to handling models and ML support. He holds a Machine Learning certification from AWS and enjoys using a variety of AWS ML services to resolve customers challenges.