amazon sagemaker

Read more

In this demo, we show how to build a smart ad display to serve relevant advertisements in real-time, based on the inference from the audience looking at the ads. Advertising displays serve static or periodically shuffling ads, which change at…

Read more

Cloud security at AWS is the highest priority. At AWS, building a secure environment from our data centers to our network architecture is of paramount importance. The same principles apply to machine learning where we provide a secure environment using…

Read more

AWS offers and delivers the broadest choice of powerful compute, high speed networking, and scalable high-performance storage options for any machine learning (ML) project or application. You can also choose the ML infrastructure to implement a fully managed ML Deployment…

Read more

This session takes you through the journey of building Enterprise Scale ML workflows on Kubernetes and Amazon SageMaker with Kubeflow Pipelines. Kubeflow is a popular open-source machine learning (ML) toolkit for Kubernetes users who want to build custom ML pipelines.…

Read more

Machine learned models and data-driven systems are being increasingly used to help make decisions in application domains such as financial services, healthcare, education, and human resources. With the goal that a significant portion of these decision systems becoming fully-automated, there…

Read more

Preparing training data is a critical step in machine learning. Preparing data involves creating labelled data, creating features, visualizing the features, and processing the data so it can be made available for training. In this session, learn how to use…

Read more

Amazon SageMaker helps data scientists and developers to prepare, build, train, and deploy high-quality machine learning (ML) models quickly by bringing together a broad set of capabilities purpose-built for ML. In this session, we provide an overview for one of…

Read more

Using data in your data warehouse for machine learning use cases like churn prediction can be complicated because of the different tools and skills required. In this session, learn how with Amazon Redshift Machine Learning, you can use SQL to…

Read more

Amazon FSx for Lustre is a high-performance file system for processing Amazon S3 or on-premises data. Learn more at - https://amzn.to/2GglrJa​. With Amazon FSx for Lustre, you can launch and run a Lustre file system that can process massive data…

Read more

In this session, learn more about Amazon SageMaker Edge Manager, a new capability of Amazon SageMaker that helps developers operate machine learning (ML) models on a fleet of edge devices and solve challenges with constraints and maintenance of ML models…