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ADM201-L - Leadership session: Digital marketing and ad technology Remember when having scaled infrastructure was a huge differentiator in marketing and ad tech? Not anymore. In this session, meant for executive leaders, you get to see the AWS vision for how companies can stand out in the crowded, massively scaled advertising and marketing ecosystem. Industry leaders will share stories about how they used AWS to enable breakthroughs in customer data collection, identity resolution, audience targeting, media buying, personalization and measurement. Then we turn to the future, and share our playbook for artificial intelligence and real-time solutions to transform big data into marketing outcomes. Session
AIM201-S - Hot paths to anomaly detection with TIBCO data science, streaming on AWS Sensor data on the event stream can be voluminous. In NAND manufacturing, there are millions of columns of data that represent many measured and virtual metrics. These sensor data can arrive with considerable velocity. In this session, learn about developing cross-sectional and longitudinal analyses for anomaly detection and yield optimization using deep learning methods, as well as super-fast subsequence signature search on accumulated time-series data and methods for handling very wide data in Apache Spark on Amazon EMR. The trained models are developed in TIBCO Data Science and Amazon SageMaker and applied to event streams using services such as Amazon Kinesis to identify hot paths to anomaly detection. This presentation is brought to you by TIBCO Software, an APN Partner. Session Steve Hillion Michael O'Connell
AIM202-S - PwC’s SENTRI solution for HC/LS case management SENTRI is an intelligent automation application platform built leveraging native AWS components to facilitate case processing in the Healthcare industry. PwC built an engine that can take in an adverse healthcare/level of service (HC/LS) event case, extract key information, provide an initial interpretation of severity, and triage the case for review. PwC performed analysis using a user-centric experience, which allowed the case processor to easily verify outputs and helped build trust and confidence in the machine’s interpretation. In this session, learn how a PwC customer has been successfully using this system for over nine months. It used to take two hours to process a case. Now, it takes three seconds. This presentation is brought to you by PwC, an APN Partner. Session Matthew Rich
AIM203-S - Take AI/ML from theory to practice with Intel technologies on AWS The challenges associated with scalability have been removed in the cloud. Today, organizations deploy tons of artificial intelligence/machine learning (AI/ML) workloads on AWS. Learn about how easy and cost-effective it is to build customized, intelligent data models leveraging the full power of Intel Xeon Scalable processors. Also, learn how you can rapidly train, deploy, and operationalize AI/ML and big data applications on AWS. This presentation is brought to you by Intel, an APN Partner. Session
AIM301-R - [REPEAT] Creating high-quality training datasets with data labeling Amazon SageMaker Ground Truth makes it easy to quickly label high-quality, accurate training datasets. In this workshop, we set up labeling jobs for text and images to help you understand how to make the most of Amazon SageMaker Ground Truth. You learn how to explore and prepare the dataset and label it with object bounding boxes. Then, we use Amazon SageMaker to train a Single Shot MultiBox Detector (SSD) object-detection model based on the labeled dataset, use hyperparameter optimization to find the best model for deployment, and deploy the model to an endpoint for use in an application. Workshop
AIM301-R1 - [REPEAT 1] Creating high-quality training datasets with data labeling Amazon SageMaker Ground Truth makes it easy to quickly label high-quality, accurate training datasets. In this workshop, we set up labeling jobs for text and images to help you understand how to make the most of Amazon SageMaker Ground Truth. You learn how to explore and prepare the dataset and label it with object bounding boxes. Then, we use Amazon SageMaker to train a Single Shot MultiBox Detector (SSD) object-detection model based on the labeled dataset, use hyperparameter optimization to find the best model for deployment, and deploy the model to an endpoint for use in an application. Workshop
AIM302-R - [REPEAT] Create a Q&A bot with Amazon Lex and Amazon Alexa A recent poll showed that 44 percent of customers would rather talk to a chatbot than to a human for customer support. In this workshop, we show you how to deploy a question-and-answer bot using two open-source projects: QnABot and Lex-Web-UI. You get started quickly using Amazon Lex, Amazon Alexa, and Amazon Elasticsearch Service (Amazon ES) to provide a conversational chatbot interface. You enhance this solution using AWS Lambda and integrate it with Amazon Connect. Workshop
AIM302-R1 - [REPEAT 1] Create a Q&A bot with Amazon Lex and Amazon Alexa A recent poll showed that 44 percent of customers would rather talk to a chatbot than to a human for customer support. In this workshop, we show you how to deploy a question-and-answer bot using two open-source projects: QnABot and Lex-Web-UI. You get started quickly using Amazon Lex, Amazon Alexa, and Amazon Elasticsearch Service (Amazon ES) to provide a conversational chatbot interface. You enhance this solution using AWS Lambda and integrate it with Amazon Connect. Workshop
AIM303-R - [REPEAT] Stop guessing: Use AI to understand customer conversations You don't need to be a data scientist to build an AI application. In this workshop, we show you how to use AWS AI services to build a serverless application that can help you understand your customers. Analyze call-center recordings with the help of automatic speech recognition (ASR), translation, and natural language processing (NLP). Get hands-on by producing your own call recordings using Amazon Connect. In the last step, you set up a processing pipeline to automate transcription and NLP analysis, and run analytics and visualizations on the results. Workshop
AIM303-R1 - [REPEAT 1] Stop guessing: Use AI to understand customer conversations You don't need to be a data scientist to build an AI application. In this workshop, we show you how to use AWS AI services to build a serverless application that can help you understand your customers. Analyze call-center recordings with the help of automatic speech recognition (ASR), translation, and natural language processing (NLP). Get hands-on by producing your own call recordings using Amazon Connect. In the last step, you set up a processing pipeline to automate transcription and NLP analysis, and run analytics and visualizations on the results. Workshop
AIM304-R - [REPEAT] Build a content-recommendation engine with Amazon Personalize Machine learning is being used increasingly to improve customer engagement by powering personalized product and content recommendations. Amazon Personalize lets you easily build sophisticated personalization capabilities into your applications, using machine learning technology perfected from years of use on Amazon.com. In this workshop, you build your own recommendation engine by providing training data, building a model based on the algorithm of your choice, testing the model by deploying your Amazon Personalize campaign, and integrating it into your own application. Workshop
AIM304-R1 - [REPEAT 1] Build a content-recommendation engine with Amazon Personalize Machine learning is being used increasingly to improve customer engagement by powering personalized product and content recommendations. Amazon Personalize lets you easily build sophisticated personalization capabilities into your applications, using machine learning technology perfected from years of use on Amazon.com. In this workshop, you build your own recommendation engine by providing training data, building a model based on the algorithm of your choice, testing the model by deploying your Amazon Personalize campaign, and integrating it into your own application. Workshop
AIM305-R - [REPEAT] Automate content moderation and compliance with AI Brand safety is a major concern as advertising becomes more automated, issues with ad adjacency arise, contracts with brands or celebrities run out, and user-generated content is more prevalent. In this workshop, you learn how to use Amazon Rekognition, Amazon Textract, and Amazon Comprehend to detect inappropriate content for moderation, or improper use of content like logos or celebrity faces for compliance. You leave with a scalable architecture that will save days of manual review in media moderation and compliance workflows. Workshop
AIM305-R1 - [REPEAT 1] Automate content moderation and compliance with AI Brand safety is a major concern as advertising becomes more automated, issues with ad adjacency arise, contracts with brands or celebrities run out, and user-generated content is more prevalent. In this workshop, you learn how to use Amazon Rekognition, Amazon Textract, and Amazon Comprehend to detect inappropriate content for moderation, or improper use of content like logos or celebrity faces for compliance. You leave with a scalable architecture that will save days of manual review in media moderation and compliance workflows. Workshop
AIM306 - Deploying machine learning models in production Amazon SageMaker is a modular service that makes it easy to build, train, and deploy machine learning models. In this session, we dive deep into how to deploy machine learning models in the cloud and on edge devices. Amazon SageMaker lets you deploy your trained model in production with a single click so that you can start generating predictions. We also explain how to reduce inference costs by up to 75 percent using Amazon Elastic Inference, and how to train models once and run them anywhere using Amazon SageMaker Neo. Come away understanding all of your options for model deployment. Session
AIM307 - Amazon SageMaker deep dive: A modular solution for machine learning Amazon SageMaker is a fully managed service that offers developers and data scientists the flexibility to build, train, and deploy machine learning models through modular capabilities. In this session, we dive deep into the technical details of each module so you understand how to label and prepare your data, choose an algorithm, train and optimize the model, and make predictions. We also discuss practical deployments of Amazon SageMaker through real-world customer examples. Session
AIM308 - Build accurate training datasets with Amazon SageMaker Ground Truth Successful machine learning models are built on high-quality training datasets. Typically, the task of labeling is distributed across a large number of humans, adding significant overhead and cost. In this session, learn how Amazon SageMaker Ground Truth reduces cost and complexity using a machine learning technique called active learning to label datasets. Active learning reduces the time and manual effort required to do data labeling, by continuously training machine learning algorithms based on labels from humans. Session
AIM401-R - [REPEAT] Deep learning with TensorFlow The TensorFlow deep-learning framework has broad support in areas such as computer vision, natural language understanding, and speech translation. You can get started with a fully managed TensorFlow experience using Amazon SageMaker, a service designed to build, train, and deploy machine learning models at scale. In this workshop, we build, train, and deploy a computer-vision model using key TensorFlow features, including distributed training with Horovod, training on pipe mode datasets, and monitoring with TensorBoard. Workshop
AIM401-R1 - [REPEAT 1] Deep learning with TensorFlow The TensorFlow deep-learning framework has broad support in areas such as computer vision, natural language understanding, and speech translation. You can get started with a fully managed TensorFlow experience using Amazon SageMaker, a service designed to build, train, and deploy machine learning models at scale. In this workshop, we build, train, and deploy a computer-vision model using key TensorFlow features, including distributed training with Horovod, training on pipe mode datasets, and monitoring with TensorBoard. Workshop
AIM402-R - [REPEAT] Deep learning with PyTorch PyTorch is a deep-learning framework that is becoming popular, especially for rapid prototyping of new models. You can get started easily with PyTorch using Amazon SageMaker, a fully managed service, to build, train, and deploy machine learning models at scale. In this workshop, we build a natural-language-processing model to analyze text. Workshop
AIM402-R1 - [REPEAT 1] Deep learning with PyTorch PyTorch is a deep-learning framework that is becoming popular, especially for rapid prototyping of new models. You can get started easily with PyTorch using Amazon SageMaker, a fully managed service, to build, train, and deploy machine learning models at scale. In this workshop, we build a natural-language-processing model to analyze text. Workshop
AIM403-R - [REPEAT] Deep learning with Apache MXNet In this workshop, learn how to get started with the Apache MXNet deep learning framework using Amazon SageMaker, a fully managed service, to build, train, and deploy machine learning models at scale. Learn how to build a computer-vision model using MXNet to extract insights from an image dataset. Once the model is built, learn how to quickly train it to get the best possible results and then easily deploy it to production using Amazon SageMaker. Workshop
AIM403-R1 - [REPEAT 1] Deep learning with Apache MXNet In this workshop, learn how to get started with the Apache MXNet deep learning framework using Amazon SageMaker, a fully managed service, to build, train, and deploy machine learning models at scale. Learn how to build a computer-vision model using MXNet to extract insights from an image dataset. Once the model is built, learn how to quickly train it to get the best possible results and then easily deploy it to production using Amazon SageMaker. Workshop
AIM404-R - [REPEAT] Reinforcement learning with Amazon SageMaker Reinforcement learning (RL) is used to build sophisticated models without the need for pre-labeled training data. In this workshop, you learn how to use the built-in, fully managed RL algorithms that are part of Amazon SageMaker RL. Amazon SageMaker supports RL in multiple frameworks, including TensorFlow and MXNet, as well as in custom-developed frameworks designed from the ground up for reinforcement learning, such as Intel Coach and Ray RLlib. Also, use Amazon SageMaker RL to train in using virtual 3D environments that are built in Amazon Sumerian and AWS RoboMaker. Workshop
AIM404-R1 - [REPEAT 1] Reinforcement learning with Amazon SageMaker Reinforcement learning (RL) is used to build sophisticated models without the need for pre-labeled training data. In this workshop, you learn how to use the built-in, fully managed RL algorithms that are part of Amazon SageMaker RL. Amazon SageMaker supports RL in multiple frameworks, including TensorFlow and MXNet, as well as in custom-developed frameworks designed from the ground up for reinforcement learning, such as Intel Coach and Ray RLlib. Also, use Amazon SageMaker RL to train in using virtual 3D environments that are built in Amazon Sumerian and AWS RoboMaker. Workshop
AIM405-R - [REPEAT] Start using computer vision with AWS DeepLens If you're new to deep learning, this workshop is for you. Learn how to build and deploy computer-vision models using the AWS DeepLens deep-learning-enabled video camera. Also learn how to build a machine learning application and a model from scratch using Amazon SageMaker. Finally, learn to extend that model to Amazon SageMaker to build an end-to-end AI application. Workshop
AIM405-R1 - [REPEAT 1] Start using computer vision with AWS DeepLens If you're new to deep learning, this workshop is for you. Learn how to build and deploy computer-vision models using the AWS DeepLens deep-learning-enabled video camera. Also learn how to build a machine learning application and a model from scratch using Amazon SageMaker. Finally, learn to extend that model to Amazon SageMaker to build an end-to-end AI application. Workshop
ALX201-R - [REPEAT] How developers can build natural, extensible voice conversations Alexa dialogue technology allows you to build multi-turn conversations that sound natural to customers; it also allows you to be a part of broader customer experiences such as seeking a recommendation or planning a night out. This session walks you through implementing Alexa dialogue technology to create rich conversational experiences. Session
ALX201-R1 - [REPEAT 1] How developers can build natural, extensible voice conversations Alexa dialogue technology allows you to build multi-turn conversations that sound natural to customers; it also allows you to be a part of broader customer experiences such as seeking a recommendation or planning a night out. This session walks you through implementing Alexa dialogue technology to create rich conversational experiences. Session
ALX201-R2 - [REPEAT 2] How developers can build natural, extensible voice conversations Alexa dialogue technology allows you to build multi-turn conversations that sound natural to customers; it also allows you to be a part of broader customer experiences such as seeking a recommendation or planning a night out. This session walks you through implementing Alexa dialogue technology to create rich conversational experiences. Session
ALX301-R - [REPEAT] Build next-generation voice-enabled devices with Alexa Are you a device maker looking to add ambient computing interfaces to your next big idea? Come get a sneak peek into the future of the Alexa Voice Service, bringing conversational AI to your unique device category. Machine learning algorithms will make your product smarter every day, and your customers will love an interface that is invisible yet available anywhere. See live demos, hear customer success stories, and learn how to accelerate your path to market. Be the first company to add voice in your device category! Workshop
ALX301-R1 - [REPEAT 1] Build next-generation voice-enabled devices with Alexa Are you a device maker looking to add ambient computing interfaces to your next big idea? Come get a sneak peek into the future of the Alexa Voice Service, bringing conversational AI to your unique device category. Machine learning algorithms will make your product smarter every day, and your customers will love an interface that is invisible yet available anywhere. See live demos, hear customer success stories, and learn how to accelerate your path to market. Be the first company to add voice in your device category! Workshop
ALX302-R - [REPEAT] Build an engaging Alexa skill with Cake Walk An engaging Alexa skill is built upon a well-thought-out design. A major part of designing the experience is mimicking an engaging human conversational partner. In this workshop, learn how to build Cake Walk, a simple skill that delights customers by wishing them happy birthday. Learn how to start with the “happy path” and use situational design for the interaction, then implement the skill. Use auto-delegation to collect information and Amazon S3 to give your skill memory. Finally, learn how to use the Alexa Settings API to look up the time zone of the device to accurately determine the customer’s birthday. Workshop
ALX302-R1 - [REPEAT 1] Build an engaging Alexa skill with Cake Walk An engaging Alexa skill is built upon a well-thought-out design. A major part of designing the experience is mimicking an engaging human conversational partner. In this workshop, learn how to build Cake Walk, a simple skill that delights customers by wishing them happy birthday. Learn how to start with the “happy path” and use situational design for the interaction, then implement the skill. Use auto-delegation to collect information and Amazon S3 to give your skill memory. Finally, learn how to use the Alexa Settings API to look up the time zone of the device to accurately determine the customer’s birthday. Workshop
ALX303 - Learn situational design with Cake Walk Design is an important part of building voice-first user interfaces. A major part of designing the experience is mimicking a human conversational partner. Even simple skills can benefit from a well-thought-out design. In this workshop you learn about situational design and how we used it to build Cake Walk, a simple skill that delights customers by wishing them happy birthday. You get the “happy path” script and walk through a series of activities to teach you how to build a situational design deck. Chalk Talk
ALX304-R - [REPEAT] Build and monetize an Alexa skill using in-skill purchasing Experienced Alexa Skills Kit builders only; must bring your laptop! In-skill purchasing (ISP) lets you sell digital content like game features, interactive stories, or hints in a trivia skill. Customers may ask to shop products, buy products by name, or agree to purchase suggestions while they interact with a skill. In this workshop, learn how to build a skill with premium content that can be unlocked via subscriptions, entitlements, and consumables. Learn the complete process, from building to testing to publishing, and monetize your skills to tap into a larger customer base, generating revenue to grow your global voice business. Builders Session
ALX304-R1 - [REPEAT 1] Build and monetize an Alexa skill using in-skill purchasing Experienced Alexa Skills Kit builders only; must bring your laptop! In-skill purchasing (ISP) lets you sell digital content like game features, interactive stories, or hints in a trivia skill. Customers may ask to shop products, buy products by name, or agree to purchase suggestions while they interact with a skill. In this workshop, learn how to build a skill with premium content that can be unlocked via subscriptions, entitlements, and consumables. Learn the complete process, from building to testing to publishing, and monetize your skills to tap into a larger customer base, generating revenue to grow your global voice business. Builders Session
ALX304-R2 - [REPEAT 2] Build and monetize an Alexa skill using in-skill purchasing Experienced Alexa Skills Kit builders only; must bring your laptop! In-skill purchasing (ISP) lets you sell digital content like game features, interactive stories, or hints in a trivia skill. Customers may ask to shop products, buy products by name, or agree to purchase suggestions while they interact with a skill. In this workshop, learn how to build a skill with premium content that can be unlocked via subscriptions, entitlements, and consumables. Learn the complete process, from building to testing to publishing, and monetize your skills to tap into a larger customer base, generating revenue to grow your global voice business. Builders Session
ALX304-R3 - [REPEAT 3] Build and monetize an Alexa skill using in-skill purchasing Experienced Alexa Skills Kit builders only; must bring your laptop! In-skill purchasing (ISP) lets you sell digital content like game features, interactive stories, or hints in a trivia skill. Customers may ask to shop products, buy products by name, or agree to purchase suggestions while they interact with a skill. In this workshop, learn how to build a skill with premium content that can be unlocked via subscriptions, entitlements, and consumables. Learn the complete process, from building to testing to publishing, and monetize your skills to tap into a larger customer base, generating revenue to grow your global voice business. Builders Session
ALX305-R - [REPEAT] Deep dive into building multimodal skills The vision of Alexa is to be everywhere. While Alexa is always voice-first, multimodal experiences can enrich the lives of your customers. In this session, we take a deep look at the capabilities of the Alexa Presentation Language (APL) and how you can use this to enrich your Alexa skills. We walk through tooling, code samples, and skills, showcasing beautiful multimodal experiences. This is an engineering-focused session. Builders Session
ALX305-R1 - [REPEAT 1] Deep dive into building multimodal skills The vision of Alexa is to be everywhere. While Alexa is always voice-first, multimodal experiences can enrich the lives of your customers. In this session, we take a deep look at the capabilities of the Alexa Presentation Language (APL) and how you can use this to enrich your Alexa skills. We walk through tooling, code samples, and skills, showcasing beautiful multimodal experiences. This is an engineering-focused session. Builders Session
ALX306-R - [REPEAT] Building robots that respond to voice In this session, learn how you can control robots with your voice through the Alexa Skills Kit. We’ll live-code with the Robot Operating System (ROS) and AWS RoboMaker to build an intelligent robotic application that responds to our voice commands to navigate autonomously in a simulated environment. Workshop
ALX306-R1 - [REPEAT 1] Building robots that respond to voice In this session, learn how you can control robots with your voice through the Alexa Skills Kit. We’ll live-code with the Robot Operating System (ROS) and AWS RoboMaker to build an intelligent robotic application that responds to our voice commands to navigate autonomously in a simulated environment. Workshop
ALX307-R - [REPEAT] Create rich, interactive displays with Alexa Presentation Language In a voice-first world, visuals can enhance interactions with Alexa-enabled devices. Learn how to improve the experience by creating interactive displays for Alexa skills with Alexa Presentation Language (APL). Workshop
ALX307-R1 - [REPEAT 1] Create rich, interactive displays with Alexa Presentation Language In a voice-first world, visuals can enhance interactions with Alexa-enabled devices. Learn how to improve the experience by creating interactive displays for Alexa skills with Alexa Presentation Language (APL). Workshop
ALX401 - Learn how to handle data in your Alexa skills Alexa skills can use data from different sources in different ways, as well as looking to store that data in different ways—but which is the best for a given use case? What tradeoffs play into that decision, and what are the best practices that should be applied? The serverless architecture of AWS Lambda aligns well with Alexa skills, but which techniques and AWS data-related services align with both these use cases and the serverless approach? You don’t need to be a DB admin (SQL, NoSQL, or otherwise) to learn how to handle data in your Alexa skills. Chalk Talk
ALX402 - Building a multimodal Alexa skill with Alexa Presentation Language Learn how to enhance your skill-building with visuals to improve the engagement and quality of your Alexa skills. Chalk Talk
ANT201-R - [REPEAT] Building workflows on AWS Lake Formation & AWS Glue Do you need to ingest and process data for analytics? Does your data have special requirements? Bring your laptop to this workshop and get hands-on experience developing workflows on AWS Lake Formation and AWS Glue. Learn how you can customize your jobs and blueprints to follow your business logic and rules to build reliable and scalable data integration for your data lake. Workshop Santosh Chandrachood Raghu Prabhu
ANT201-R1 - [REPEAT 1] Building workflows on AWS Lake Formation & AWS Glue Do you need to ingest and process data for analytics? Does your data have special requirements? Bring your laptop to this workshop and get hands-on experience developing workflows on AWS Lake Formation and AWS Glue. Learn how you can customize your jobs and blueprints to follow your business logic and rules to build reliable and scalable data integration for your data lake. Workshop Raghu Prabhu Santosh Chandrachood
ANT202-R - [REPEAT] Turbocharge your Spark performance with Amazon EMR Are you considering running Spark on Amazon EMR and want to understand how Amazon EMR can deliver out-of-box performance for Apache Spark at the lowest cost? In this chalk talk discussion, we focus on Spark improvements, using auto scaling to improve Spark performance. Bring your questions, and learn from the experts. Chalk Talk Paul Codding Joseph Marques
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