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89815 - [REPEAT 1] Iterating Towards a Cloud-Enabled IT Organization Transforming your organization and its people to become cloud-natives can be an overwhelming task. Platform teams, operations teams, development teams, and their even their leaders have non-technical challenges to consider and overcome to unlock the maximum value of running their businesses on AWS. In this chalk talk you’ll learn how to combine Amazonian ways of working, organizing, and enabling to kickstart your cloud journey with a “Cloud Foundation Team” and a small number of “Two-Pizza Application Teams”, and also how to then iteratively scale the concepts used to build these initial teams into a fully cloud-enabled IT organization. Chalk Talk
89887 - [REPEAT 2] Build the Next-Gen Meeting Room Experience Using Alexa for Business Alexa for Business brings a conversational UI to help you simplify your meeting room experience. In this session, learn how you can bring Alexa for Business to your meeting room and integrate it with your existing meeting room systems. In addition, the Amazon IT team discusses best practices, and they describe how they piloted and deployed Alexa for Business in over 5,000 conference rooms at Amazon.  Session
89926 - [REPEAT 1] Create a Custom Celebrity List for Your Media Assets When indexing large amounts of media files, it can become difficult to search through them to find certain objects and individuals. In this session, we show you how creating a custom celebrity list enables you to index your media files by the people you train it to recognize. Come and see how this solution can serve as the foundation for creating automated sports highlight reels, building face-based user verification systems, and more. Chalk Talk
90257 - [REPEAT 1] Make Money with Alexa Skills By creating a monetized Alexa skill from scratch, developers in this session learn how to leverage Alexa in-skill purchasing APIs, Amazon Pay, and developer reporting tools to help unlock premium digital content in a custom voice experience. See how in-skill purchasing enables customers and developers the flexibility of payment through a subscription, and one-time entitlement. Dive deep, and leave this session with everything you need to know to make money with Alexa skills. Session
90265 - [REPEAT 1] Everything You Wanted to Know about Developing for Voice Using Alexa In this chalk talk, we review the common challenges developers face when building voice experiences for Alexa. We provide an overview of the history of design in technology, highlighting what we learned over the years in developing for a screen. We also establish best practices for voice-first design using the Alexa Skills Kit, which we contrast with GUI design principles. You have the opportunity to ask questions and discuss ideas among fellow skill developers. By the end of this session, expect to understand the similarities and differences between developing for voice and developing for screen-oriented mediums. Chalk Talk
90683 - [REPEAT 1] How to Train Your Alexa Skill Language Model Using Machine Learning In order to create an engaging Alexa skill, you must have a well-thought-out language model for your voice UI. In this session, learn how to make your Alexa skill more delightful to customers by optimizing your language model, providing the correct training data for your custom intents, and using specific strategies to improve new and existing language models. Come prepared for an interactive conversation. Chalk Talk
90746 - [REPEAT 1] Create Immersive Experiences Using Amazon Sumerian Anyone can create and publish augmented reality (AR), virtual reality (VR), and 3D applications quickly and easily with Amazon Sumerian. In this session, learn how to use Sumerian to build a scene that can be published and viewed on laptops, mobile phones, VR headsets, and digital signage. Take a tour of the Sumerian interface, and learn how to build a scene, add assets and hosts, and add behaviors to create dynamically animated objects and characters in an AR/VR experience. Also see how Sumerian integrates into AWS services such as Amazon Polly, Amazon Lex, AWS Lambda, Amazon S3, and Amazon DynamoDB. Session
90859 - Build Human-in-the-Loop Systems with Amazon Lambda and Amazon Mechanical Turk Building human-in-the-loop solutions can be very effective, but integrating humans into existing ML or business process workflows can be complex. Learn how you can easily connect MTurk's on-demand human intelligence platform with other AWS services like Amazon S3, Amazon Lex, Amazon Polly, and Amazon Rekognition via AWS Lambda. Builders Session
90919 - [REPEAT 1] Capture Voice of Customer Insights with NLP & Analytics Understanding your customers is easier today than ever before. Natural language capabilities can capture a wealth of information, such as user sentiment and conversational intent. This workshop teaches you how to build an analytics pipeline that includes natural language processing (NLP) to better understand how to improve the customer experience. Attendees learn how to use AWS services, including Amazon Comprehend and Amazon Transcribe, to process and perform analysis on customer data, such as contact center call recordings. Workshop
90922 - [REPEAT 1] Build Multichannel Conversational Interfaces Using Amazon Lex Learn how to build a multichannel conversational interface that uses a preprocessing layer in front of Amazon Lex, or route messages to other specialized bots. Amazon Lex offers built-in integrations with Slack, Twilio, Marketo, Salesforce, QuickBooks, Microsoft Dynamics, Zendesk, and HubSpot. Also learn how to integrate with any other application by combining the Amazon Lex API and Amazon API Gateway to integrate your Amazon Lex bot with any messaging service. Builders Session
90923 - [REPEAT 1] Machine Learning Transcription: Tips & Tricks Amazon Transcribe is an automatic speech recognition service that makes it easy for developers to add speech-to-text capability to their applications. Join us and learn how you can build machine transcription into your existing workflows, such as transcribing videos for search engines or captioning. Builders Session
91062 - [REPEAT 3] Deep Learning Applications Using TensorFlow and Amazon SageMaker The TensorFlow deep learning framework is used for developing diverse AI applications including computer vision, natural language, speech, and translation. In this session, learn how to use TensorFlow within the Amazon SageMaker machine learning platform. This code-level session also includes tutorials and examples using TensorFlow. Session
91095 - [REPEAT 2] Build Deep Learning Applications Using Apache MXNet and Amazon SageMaker The Apache MXNet deep learning framework is used for developing, training, and deploying diverse AI applications, including computer vision, speech recognition, natural language processing, and more at scale. In this session, learn how to get started with Apache MXNet on the Amazon SageMaker machine learning platform. This code-level session includes tutorials and examples using MXNet. Session
91099 - [REPEAT 2] Deep Learning for Developers: An Introduction Deep learning has the potential to enable extremely advanced AI applications. But it's not taught in most computer science programs, and you may have a lot of questions. In this session, understand how deep learning works, and learn key concepts such as neural networks, activation functions, and optimizers. We show you how deep learning models improve through complex pattern recognition in pictures, text, sounds, and other data to produce more accurate insights and predictions. We also share examples of common deep learning use cases, such as computer vision and recommendation models. Finally, we help you understand how to get started using popular deep learning frameworks, such as TensorFlow, Apache MXNet, and PyTorch. Session
91103 - [REPEAT 2] Amazon SageMaker and TensorFlow: Tips & Tricks In this session, learn how to use TensorFlow in the Amazon SageMaker machine learning platform. Builders Session
91105 - [REPEAT 3] Amazon SageMaker and TensorFlow: Tips & Tricks In this session, learn how to use TensorFlow in the Amazon SageMaker machine learning platform. Builders Session
91107 - [REPEAT 2] Amazon SageMaker and Apache MXNet: Tips & Tricks In this session, learn how to use Apache MXNet in the Amazon SageMaker machine learning platform. Builders Session
91108 - [REPEAT 2] Amazon SageMaker and PyTorch: Tips & Tricks In this session, learn how to use PyTorch in the Amazon SageMaker machine learning platform. Builders Session
91109 - [REPEAT 3] Amazon SageMaker and PyTorch: Tips & Tricks In this session, learn how to use PyTorch in the Amazon SageMaker machine learning platform. Builders Session
91110 - [REPEAT 1] Amazon SageMaker and Chainer: Tips & Tricks In this session, learn how to use Chainer, an open-source deep learning framework written in Python, in the Amazon SageMaker machine learning platform. Builders Session
91124 - [REPEAT 1] Hands-On: Building a Multi-Region Active-Active Solution Join us as we build and verify a global application that spans multiple regions using AWS data, storage, and compute services. Workshop
91126 - [REPEAT 2] Perform Diagnostics on Running Instances without Affecting Availability/Reliability In this Builder Session, we demonstrate how remove an instance from an auto-scaling group. We use AWS Service Catalog to provision a bastion, and then we use AWS Systems Manager to provision SSH access for a limited time to perform diagnostics. When we complete, access will be removed, and the bastion will be decommissioned. Attendees need an account that can provision AWS Lambda, Amazon EC2, AWS Service Catalog, AWS Systems Manager, and Amazon CloudWatch Events. Builders Session
91129 - [REPEAT 1] Reliability of the Cloud: How AWS Achieves High Availability In this chalk talk, we explore the implementation details of achieving availability and reliability, as described in the whitepaper, AWS Well-Architected Framework - Reliability Pillar Chalk Talk
AIM201 - [REPEAT] Machine Learning for the Enterprise Leading companies are using machine learning (ML) to power innovation across industries, including healthcare, automotive, and finance. In this session, learn how to build scalable ML solutions using the Amazon SageMaker platform, as well as our services for computer vision, language, and analytics. We also demonstrate real-world use cases for enterprises to get more value from their data and integrate and manage intelligent systems and processes. Session
AIM202 - Leadership Session: Machine Learning Amazon has a long history in AI, from personalization and recommendation engines to robotics in fulfillment centers. Amazon Go, Amazon Alexa, and Amazon Prime Air are also examples. In this session, learn more about the latest machine learning services from AWS, and hear from customers who are partnering with AWS for innovative AI. Session
AIM203 - Applying AI for Real-World Outcomes Modeling at Amgen on AWS Are you curious about how AWS machine learning can enable healthcare organizations to find the insights they need to survive and thrive? Through Deloitte's ConvergeHEALTH Deep Miner platform powered by AWS, Amgen can now analyze data faster and reduce patient recovery time. Join us to learn more about how Amgen researchers built and trained their own disease-specific machine learning models, including deep learning models using Deloitte's ConvergeHEALTH platform, to simulate and quantify overall disease burden and identify potential risks for patients. This session is brought to you by AWS partner, Deloitte Consulting LLP. Session
AIM204 - Smarter event-driven edge with Amazon SageMaker & Project Flogo A single device can produce thousands of events every second. In traditional implementations, all data is transmitted back to a server or gateway for scoring by a machine learning (ML) model. This data is also stored in a data repository for later use by data scientists. In this session, we explore data science techniques for dealing with time series data leveraging Amazon SageMaker. We also look at modeling applications using deterministic rules with streaming pipelines for data prep, and model inferencing using deep learning frameworks directly onto edge devices or onto AWS Lambda using Project Flogo, an open-source event-driven framework. This session is brought to you by AWS partner, TIBCO Software Inc. Session
AIM301 - [REPEAT] Deep Learning for Developers: An Introduction Deep learning has the potential to enable extremely advanced AI applications. But it's not taught in most computer science programs, and you may have a lot of questions. In this session, understand how deep learning works, and learn key concepts such as neural networks, activation functions, and optimizers. We show you how deep learning models improve through complex pattern recognition in pictures, text, sounds, and other data to produce more accurate insights and predictions. We also share examples of common deep learning use cases, such as computer vision and recommendation models. Finally, we help you understand how to get started using popular deep learning frameworks, such as TensorFlow, Apache MXNet, and PyTorch. Session
AIM302 - Machine Learning at the Edge Video-based tools have enabled advancements in computer vision, such as in-vehicle use cases for AI. However, it is not always possible to send this data to the cloud to be processed. In this session, learn how to train machine learning models using Amazon SageMaker and deploy them to an edge device using AWS Greengrass, enabling you process data quickly at the edge, even when there is no connectivity. Session
AIM303 - [REPEAT] Create Smart and Interactive Apps with Intelligent Language Services on AWS Amazon brings natural language processing, automatic speech recognition, text-to-speech services, and neural machine translation technologies within the reach of every developers. In this session, learn how to add intelligence to any application with machine learning services that provide language and chatbot functions. See how others are defining and building the next generation of apps that can hear, speak, understand, and interact with the world around us. Session
AIM304 - Transform the Modern Contact Center Using Machine Learning and Analytics Analyzing customer service interactions across channels provides a complete 360-degree view of customers. By capturing all interactions, you can better identify the root cause of issues and improve first-call resolution and customer satisfaction. In this session, learn how to use machine learning to quickly process and analyze thousands of customer conversations to gain valuable insights. With speech and text analytics, you can pick up on emerging service-related trends before they get escalated or identify and address a potential widespread problem at its inception. Session
AIM305 - [REPEAT] Automatically Extract Metadata Using Computer Vision & Language AI Services Customers are using automatic metadata extraction to fuel new insights and provide innovative services to their customers. In this session, we walk through the basic architecture patterns for implementing automatic metadata extraction using Amazon Rekognition, Amazon Transcribe, and Amazon Comprehend. We also share how to get started with the pre-configured AWS Media Analysis Solution. Builders Session
AIM306 - [REPEAT] Build Custom Models for AWS DeepLens with Amazon SageMaker In this session, you will learn how to build and deploy computer vision models using the AWS DeepLens deep-learning-enabled video camera and Amazon SageMaker. Builders Session
AIM307 - [REPEAT] Deep Dive on Amazon Rekognition Join us for a deep dive on the latest features of Amazon Rekognition. Learn how to easily add intelligent image and video analysis to applications in order to automate manual workflows, enhance creativity, and provide more personalized customer experiences. We share best practices for fine-tuning and optimizing Amazon Rekognition for a variety of use cases, including moderating content, creating searchable content libraries, and integrating secondary authentication into existing applications. Session
AIM308 - [REPEAT] AWS DeepLens Projects: Tips & Tricks In this session, get general help on how to build or extend a project with AWS DeepLens. Builders Session
AIM310 - Build State-Of-the-Art NLP Models Using the Gluon API for Apache MXNet Implementing natural language processing (NLP) models just got simpler and faster. In this chalk talk, learn how to implement NLP models using MXNet and the Gluon NLP toolkit, which provides implementations of state-of-the-art deep learning algorithms in NLP to help engineers, researchers, and students quickly prototype products, validate new ideas, and learn natural language processing. Chalk Talk
AIM313 - Build a Babel Fish with Machine Learning Language Services In the novel, “The Hitchhiker's Guide to the Galaxy,” Douglas Adams described a Babel fish as a “small, yellow, and leech-like” device that you stick in your ear. In Star Trek, it is known simply as the universal language translator. Whatever you call it, there is no doubting the practical value of a device that is capable of translating any language into another. In this workshop, learn how to build a babel fish mobile app that recognizes voice and converts it to text (speech-to-text), translates the text to a language of your choice, and converts translated text to synthesized speech (text-to-speech). Workshop
AIM314 - Create a Question and Answer Bot with Amazon Lex and Alexa A recent poll showed that 44% of customers would rather talk to a chatbot than a to human for customer support. In this workshop, we show you how to build a QnA bot (question and answer bot) that uses Amazon Lex and Alexa to provide a conversational interface for your customers to ask questions and get relevant answers quickly. We also show you how to use Amazon Elasticsearch Service on the backend to find the best matches to answer questions. Workshop
AIM315 - [REPEAT] Deep Learning for Edge to Cloud In this workshop, you step into the role of a startup that has assumed the challenge of providing a new type of EDM music festival experience. Your goal is to use machine learning (ML) and IoT to develop a connected fan experience that enhances the festival. Come and get hands-on experience with Amazon SageMaker with Intel C5 instances, AWS DeepLens, AWS Greengrass, Amazon Rekognition, and AWS Lambda as you build and deploy an ML model and then run inference on it from the cloud and from edge devices. Workshop
AIM317 - [REPEAT] Scalable Text Mining for ETL Solutions While many ETL tools can handle structured data, very few can reliably process unstructured data and documents. In this session, learn how you can use Amazon Comprehend to address unstructured data extraction and transformation at scale so that key information can be extracted and used downstream for data integration and analytics. Builders Session
AIM318 - [REPEAT] Create the Voices You Want with Amazon Polly Many of today's text-to-speech systems limit your choices to a few voices. If these voices aren't right for your needs, the process of adding more voices is usually costly and time consuming. Learn how you can use Amazon Polly for speech production and to modify voices for a range of uses, from game development and telephony to web publishing. Builders Session
AIM319 - [REPEAT] Build Multichannel Conversational Interfaces Using Amazon Lex Learn how to build a multichannel conversational interface that uses a preprocessing layer in front of Amazon Lex, or route messages to other specialized bots. Amazon Lex offers built-in integrations with Slack, Twilio, Marketo, Salesforce, QuickBooks, Microsoft Dynamics, Zendesk, and HubSpot. Also learn how to integrate with any other application by combining the Amazon Lex API and Amazon API Gateway to integrate your Amazon Lex bot with any messaging service. Builders Session
AIM320 - [REPEAT] Machine Learning Transcription: Tips & Tricks Amazon Transcribe is an automatic speech recognition service that makes it easy for developers to add speech-to-text capability to their applications. Join us and learn how you can build machine transcription into your existing workflows, such as transcribing videos for search engines or captioning.   Builders Session
AIM321 - Improve Your Customer Experience with Machine Translation Machine Translation powers Amazon’s international expansion. Sign up to learn how you can leverage Amazon Translate to increase customer satisfaction, cut down response times, and build a more efficient customer support operation. For example, you can add real-time translation to chat, email, and helpdesk so an English-speaking agent can communicate with customers in their preferred language, or translate your knowledge base into multiple languages to make it accessible to customers and employees around the world.   Chalk Talk
AIM322 - [REPEAT] Integrate Language Services: Tips & Tricks Amazon brings natural language processing, automatic speech recognition, text-to-speech, and neural machine translation technologies within reach of every developer. Come to this session and learn how to build smarter applications or automate workflows with AWS language services. Builders Session
AIM323 - [REPEAT] Build a Searchable Image Library with Amazon Rekognition Join us for a deep dive on building a searchable image library using Amazon Rekognition. We walk though creating a search index for objects and scenes so you can quickly retrieve images using labels created from automatic metadata extraction. Also learn how to use AWS Lambda to automatically maintain your image library. Builders Session
AIM324 - [REPEAT] Analyze Live Video Streams with Amazon Rekognition Video In this session, learn how to use Amazon Rekognition Video with Amazon Kinesis to receive and process video streams. We walk through recognizing faces, giving access to Amazon Kinesis Data Streams, as well as starting and reading the streaming video analysis. Whether you are building a "Who's Who" app similar to the royal wedding, or you need to identify athletes in real time, it is simple to add intelligent video analysis to your live streams using Amazon Rekognition. Builders Session
AIM325 - [REPEAT] Amazon SageMaker: Prebuilt Algorithms In this session, learn how to use the range of built-in, high-performance machine learning algorithms that come with Amazon SageMaker. Builders Session
AIM326 - [REPEAT] Amazon SageMaker and TensorFlow: Tips & Tricks In this session, learn how to use TensorFlow in the Amazon SageMaker machine learning platform. Builders Session
AIM327 - [REPEAT] Amazon SageMaker and Apache MXNet: Tips & Tricks In this session, learn how to use Apache MXNet in the Amazon SageMaker machine learning platform. Builders Session
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