Amazon Web Services, Inc.

Women in Big Data - AWS AI/ML Workshop Minneapolis

Overview

You are invited to introductory and technical sessions including hands-on experience on the AWS Artificial Intelligence/Machine Learning Platform, hear success stories from our guest speakers, and connect with the AWS subject matter experts who can help you accelerate your machine learning efforts.

AWS has a long and rich heritage of Machine Learning and Deep Learning Solutions such as personalized shopping recommendations, automated fulfillment and inventory management, robotic drones for fast delivery, a checkout-free computer vision retail experience with Amazon Go, voice interactions with Alexa, and a lot more. And now, AWS is the center of gravity for Artificial Intelligence/Machine Learning because of the massive volume of data stored and processed on our Big Data platform. By lowering the barriers for AI/ML workloads with an innovative suite of products and services, AWS enables you to easily build machine learning powered smart applications to meet complex business needs.

Who should attend?

Solutions Architects, Developers, Technical Managers, and Decision Makers who want to understand the fundamentals of the AWS Machine Learning Platform.
Data Scientists, Architects, and Analysts looking to accelerate their AI/ML initiatives.
Machine Learning enthusiasts, women in technology or big data looking to jump-start their career in AI/ML technologies.

Event Details

Date & Time:	April 25, 2019 1:00 PM – 5:00 PM Registration: 12:30 PM
Location:	Amazon Web Services, 323 N. Washington Ave. 7th Floor, Minneapolis, MN 55401

Agenda

Time	Session
1:00 PM – 1:45 PM	Overview of AI/ML Services on AWS Short AI/ML Demo The Amazon AI/ML Stack An Introduction to Amazon SageMaker
1:45 PM – 2:20 PM	Panel Discussion with Guest Speakers Carmen Fontana, Cloud & Emerging Tech Lead at Centric Consulting Laura Madsen, Founder and President of Route Twenty Five
The following breakout sessions can be selected based on your current expertise and/or interest:
	Track 1: Hands-on Sessions for AWS AI/ML Application Services	Track 2: Hands-on Sessions for Amazon SageMaker
2:30 PM – 3:15 PM	Build your first conversational bot using Amazon Lex/Polly Level: Beginner Amazon Lex is a service that allows developers to build conversational interfaces for voice and text into applications. With Amazon Lex, the same deep learning technologies that power Amazon Alexa are now available to any developer, so you can quickly and easily build sophisticated, natural language conversational bots (chatbots). Amazon Lex’s advanced deep learning technology provides automatic speech recognition (ASR), for converting speech to text, and natural language understanding (NLU), to recognize the intent of the text so that you can build applications with highly engaging user experience. In this hands-on session, you will build a transactional conversational bot that talks to you using Amazon Polly and Amazon Lex.	Build a Prediction Model using Amazon SageMaker Built-in Algorithms Level: Intermediate Amazon SageMaker is a fully-managed service that enables data scientists and developers to quickly and easily build, train, and deploy machine learning models, at scale. In this hands-on session, you will spin up a zero-setup Jupyter notebook environment for data exploration and preparation and explore features of Amazon SageMaker including a one-click distributed training environment, highly-optimized machine learning algorithms with built-in model tuning, and deployment without engineering effort. You will use one of the built-in algorithms to train your model, deploy it to a managed endpoint and evaluate your predictions.
3:15 PM – 4:00 PM	Social Media and Amazon Rekognition Level: Intermediate Amazon Rekognition, a deep learning-based service, makes it easy to add image and video analysis to your applications. In this hands-on session, you will develop a solution that will stream and analyze social media images using Amazon Rekognition features. The solution will entail a repeatable and automated process that follows best practices for architecting in the cloud, such as designing for high availability and scalability.	Amazon SageMaker Integration with Apache Spark on Amazon EMR Level: Advanced Apache Spark has been a framework of choice for many years to address challenges for complex analysis of data. In this hands-on session, you will gain a deep understanding of Apache Spark and SageMaker integration and learn how to use the SageMaker-Spark SDK in a notebook instance. You will focus on using Apache Spark for pre-processing data and Amazon SageMaker for model training and hosting.
4:00 PM – 5:00 PM	Networking / Happy Hour

Time	Session
1:00 PM – 1:45 PM	Overview of AI/ML Services on AWS Short AI/ML Demo The Amazon AI/ML Stack An Introduction to Amazon SageMaker
1:45 PM – 2:20 PM	Panel Discussion with Guest Speakers Dr. Clare Gollnick, Chief Technology Officer at Terbium Labs Miriam McLemore, Director, Enterprise Strategy at AWS
The following breakout sessions can be selected based on your current expertise and/or interest:
	Track 1: Hands-on Sessions for AWS AI/ML Application Services	Track 2: Hands-on Sessions for Amazon SageMaker
2:30 PM – 3:15 PM	Build your first conversational bot using Amazon Lex/Polly Level: Beginner	Build a Prediction Model using Amazon SageMaker Built-in Algorithms Level: Intermediate
3:15 PM – 4:00 PM	Social Media and Amazon Rekognition Level: Intermediate	Amazon SageMaker Integration with Apache Spark on Amazon EMR Level: Advanced
4:00 PM – 5:00 PM	Networking / Happy Hour

Featured Partner

Women in Big Data - AWS AI/ML Workshop Minneapolis

Women in Big Data - AWS AI/ML Workshop Minneapolis

Event Details

Agenda

Featured Partner

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