×

You're seconds away from unlocking all AI/ML resources

First Name
Last Name
Company Name
Country
CDN Province
US State
India State
AU State
Phone Number
Job Role
Job Title
Industry
Postal Code
This information is associated with my:
Compliance Opt-in
Thank you!
Error - something went wrong!

Train ML models quickly and cost-effectively with Amazon SageMaker

March 22, 2022

In this session, learn how to reduce time and cost to train and tune machine learning (ML) models without the need to manage infrastructure. We explain how Amazon SageMaker can easily train and tune ML models using built-in tools to manage and track training experiments, automatically choose optimal hyperparameters, debug training jobs, and monitor the utilization of system resources such as GPUs, CPUs, and network bandwidth. We go through how to add either data parallelism or model parallelism to your training script with a few lines of code, and the Amazon SageMaker distributed training libraries automatically split models and training datasets across GPU instances to help you complete distributed training faster.
Speaker: Alex Thewsey, AI/ML Specialist Solutions Architect, AWS

Download slides and demo

Previous Video
Build machine learning models with Amazon SageMaker optimal for your use case
Build machine learning models with Amazon SageMaker optimal for your use case

Amazon SageMaker helps data scientists and developers to prepare, build, train, and deploy high-quality mac...

Next Video
Bias detection and explainability in ML
Bias detection and explainability in ML

Machine learning is increasingly used to assist decision making in financial services, education, transport...