German news giant WELT attracts 23.6 million unique visitors every month. Find out how the Axel Springer-owned title worked with SPRYLAB to achieve increased dwell time using AI-based links.

Speaker: Stephan Heck, CEO, Sprylab

Level: 100 (Foundational)

Duration: 19:13 min

The Machine Learning Process: From Business Model to ML in Production Session Abstract: ML offers amazing potential, but how can businesses benefit from it? How can companies identify ML opportunities and build ML into their business models? This presentation takes a methodical approach to finding ML opportunities: from asking the right questions, to collecting business data, to implementing a ML workflow. Amazon and AWS customer examples will be used to illustrate different steps, enabling you to start identifying ML opportunities immediately.

Speaker: Constantin Gonzalez, Principal Solutions Architect, AWS + Mariano Kamp, Principal Solutions Architect, AWS

Level: 200 (Intermediate)

Duration: 59:52 min

Let’s Get Personal: Improve User Engagement with Amazon Personalize Session Abstract: At Amazon, we’ve always provided our customers with product recommendations and a personalized experience. Now, using Amazon Personalize – a fully managed recommendation and personalization service – you can leverage our experience for your business. Use Amazon Personalize to increase sales and engagement for your platform and services – with no ML expertise required! This session will provide you with a technical deep dive, a demo, and guidance on how to get started.

Speaker: Johannes Langer, Senior Solutions Architect, AWS

Level: 200 (Intermediate)

Duration: 45:07 min

Amazon SageMaker provides developers and data scientists with the ability to build, train, and deploy ML models quickly and at scale. It takes away the heavy lifting of ML, removing traditional barriers. In this session, you’ll learn how to leverage Amazon SageMaker GroundTruth to build your own dataset; train an object detection model; and deploy it on an edge device such as AWS DeepLens.

Speaker: Tasio Guevara, Senior Solutions Architect, AWS

Level: 300 (Advanced)

Duration: 55:14 min

Companies spend significant time developing, searching, and evaluating algorithms and models to solve business problems using machine learning. AWS Marketplace recently launched a machine learning category which has hundreds of algorithms and model packages, that can be deployed quickly onto Amazon SageMaker, a fully-managed service that provides the ability to build, train, and deploy machine learning models. In this tech talk, we will give an introduction to AWS Marketplace for Machine Learning, and how you can get solve your business problems using 3rd party algorithms and model packages faster with less effort and lower cost. We will walk through samples Jupyter Notebooks that you can use to experiment with model packages and algorithms from AWS Marketplace.

Speaker: Kanchan Waikar, Solutions Architect, AWS Marketplace

Level: 200 (Intermediate)

Duration: 50:12 min

Machine Learning is the art of using historical data to predict the future. But how can you use historic, 'ground truth' data when the 'ground' is constantly moving? In this session, presented by Cloudreach you’ll learn how to use AWS to build a fully automated machine learning model using live-streaming data. Watch this webinar for a live demo using Amazon SageMaker for building a Machine Learning model to predict whether buying Bitcoin at a particular point of time is likely to result in profit or loss.

Speaker: Yoyu Li, Senior Cloud Data Architect, Cloudreach

Level: 300 (Advanced)

Duration: 39:25 min