講師: Jhen-Wei Huang, Solutions Architect, Amazon Web Services
Do your customers love you?
Recommendations and Voice of Customer
Analytics and AI with AWS
AWS reInvent 2017 recap - Optimizing Costs as You Scale on AWSAmazon Web Services
The cloud offers a first-in-a-career-opportunity to constantly optimize your costs as you grow and stay on the bleeding edge of innovation. By developing a cost-conscious culture and assigning the responsibility for efficiency to the appropriate business owners, you can deliver innovation efficiently and cost effectively. This session will review a wide range of cost planning, monitoring, and optimization strategies featuring real-world experience from AWS customers.
What are the different options for a developer to run his DB in the Cloud? This session will look into the different options and how to choose the right DB for your workload.
Create an ML Factory in Financial Services with CI CD - FSI301 - New York AWS...Amazon Web Services
Financial institutions want to accelerate and scale their use of machine learning (ML), but going from a hypothesis to a working ML model that infers answers in production requires much time and effort. Continuous integration and deployment techniques can help by accelerating the ML development process while providing a way to answer questions about data lineage, such as, “What version of the code and data produced this particular inference?” In this session, learn how to combine Amazon SageMaker with AWS CodeCommit, AWS CodeBuild, and AWS CodePipeline to create a workflow that helps provide the reproducibility and auditability that financial institutions need without constraining the tools and methods that data scientists use to build their ML models.
Build Data Driven Apps with Real-time and Offline CapabilitiesAmazon Web Services
All application developers today need to be concerned with offline access, realtime communications and efficient data fetching. These techniques are no longer optional for great user experiences yet are difficult to engineer and scale from scratch. In this session you’ll get a deep dive on using AWS AppSync to enable your applications for offline access, including optimistic updates on lossy connections, with just a few lines of code. You’ll learn how application data synchronization takes place with the cloud, how you can control the process, programming interfaces for native applications such as iOS and JavaScript based applications across the web, React Native, and Ionic. Additionally you’ll see how using GraphQL enables your application to efficiently leverage the network for queries and mutations while still having a scalable and fast connection for realtime updates when using subscriptions to data changes.
AWS Lambda enables you to run code without provisioning or managing servers. AWS Lambda@Edge enables you to write Lambda functions once and execute them wherever your viewers are located. In this session, we walk through examples of web applications that use the serverless programming model for authentication, customization, and security. We show you how to design and deploy intelligent web applications using Lambda@Edge and Amazon CloudFront.
AWS reInvent 2017 recap - Optimizing Costs as You Scale on AWSAmazon Web Services
The cloud offers a first-in-a-career-opportunity to constantly optimize your costs as you grow and stay on the bleeding edge of innovation. By developing a cost-conscious culture and assigning the responsibility for efficiency to the appropriate business owners, you can deliver innovation efficiently and cost effectively. This session will review a wide range of cost planning, monitoring, and optimization strategies featuring real-world experience from AWS customers.
What are the different options for a developer to run his DB in the Cloud? This session will look into the different options and how to choose the right DB for your workload.
Create an ML Factory in Financial Services with CI CD - FSI301 - New York AWS...Amazon Web Services
Financial institutions want to accelerate and scale their use of machine learning (ML), but going from a hypothesis to a working ML model that infers answers in production requires much time and effort. Continuous integration and deployment techniques can help by accelerating the ML development process while providing a way to answer questions about data lineage, such as, “What version of the code and data produced this particular inference?” In this session, learn how to combine Amazon SageMaker with AWS CodeCommit, AWS CodeBuild, and AWS CodePipeline to create a workflow that helps provide the reproducibility and auditability that financial institutions need without constraining the tools and methods that data scientists use to build their ML models.
Build Data Driven Apps with Real-time and Offline CapabilitiesAmazon Web Services
All application developers today need to be concerned with offline access, realtime communications and efficient data fetching. These techniques are no longer optional for great user experiences yet are difficult to engineer and scale from scratch. In this session you’ll get a deep dive on using AWS AppSync to enable your applications for offline access, including optimistic updates on lossy connections, with just a few lines of code. You’ll learn how application data synchronization takes place with the cloud, how you can control the process, programming interfaces for native applications such as iOS and JavaScript based applications across the web, React Native, and Ionic. Additionally you’ll see how using GraphQL enables your application to efficiently leverage the network for queries and mutations while still having a scalable and fast connection for realtime updates when using subscriptions to data changes.
AWS Lambda enables you to run code without provisioning or managing servers. AWS Lambda@Edge enables you to write Lambda functions once and execute them wherever your viewers are located. In this session, we walk through examples of web applications that use the serverless programming model for authentication, customization, and security. We show you how to design and deploy intelligent web applications using Lambda@Edge and Amazon CloudFront.
Modern data is massive, quickly evolving, unstructured, and increasingly hard to catalog and understand from multiple consumers and applications. This presentation will guide you though the best practices for designing a robust data architecture, highlightning the benefits and typical challenges of data lakes and data warehouses. We will build a scalable solution based on managed services such as Amazon Athena, AWS Glue, and AWS Lake Formation.
Building Content Recommendation Systems Using Apache MXNet and Gluon - MCL402...Amazon Web Services
Recommendations are becoming an integral part of how many business serve customers, from targeted shopping on demand video. In this session, you’ll learn the key elements to build a recommendation system using Gluon, the new intuitive, dynamic programming interface for Apache MXNet. You’ll use matrix factorization techniques to build a video on-demand solution using deep learning.
SRV309 AWS Purpose-Built Database Strategy: The Right Tool for the Right JobAmazon Web Services
In this session, Shawn Bice, VP of NoSQL and QuickSight, covers the AWS purpose-built strategy for databases and explains why your application should drive the requirements of a database, not the other way around. We introduce AWS databases that are purpose-built for your application use cases. Learn why you should select different data services to solve different aspects of an application, and watch a demonstration on which application use cases lend themselves well to which data services. If you’re a developer building modern applications that require flexibility and consistent millisecond performance, and you’re trying to determine what relational and non-relational data services to use, this session is for you.
SRV317 Creating and Publishing AR and VR Apps with Amazon SumerianAmazon Web Services
Amazon Sumerian lets anyone create and run augmented reality (AR), virtual reality (VR), and 3D applications quickly and easily without requiring specialized programming or 3D graphics expertise. In this session, participants learn how to use Sumerian to build a scene that is viewable on laptops, mobile phones, VR headsets, and digital signage. Ben Moore provides a guided overview of the Sumerian interface to create a scene, add objects, and include hosts. He then demonstrates how to manipulate assets and add behaviors to create dynamically animated objects and characters in an AR/VR experience. Finally, he covers how Sumerian integrates into AWS services such as Amazon Polly, Amazon Lex, AWS Lambda, Amazon S3, and Amazon DynamoDB.
Big Data, Analytics and Machine Learning on AWS Lambda - SRV402 - re:Invent 2017Amazon Web Services
AWS Lambda is a great fit for many data processing tasks, for data analytics and for machine learning inference. The Lambda team use Lambda for our own Analytics in conjunction with other AWS services. In this session, we will cover how we tie these services together to crunch the data Lambda creates to generate insights to better run our service. We will cover common design patterns for big data processing, how they map to Lambda and serverless, and look at some new patterns that serverless makes possible. Finally we will look to how to leverage Machine Learning inference on Lambda to derive better insights from the data.
Move your Desktops and Apps to AWS with Amazon WorkSpaces and AppStream 2 Amazon Web Services
IT organizations today need to support a modern, flexible, global workforce and ensure that their users can be productive anywhere. Moving desktops and applications to the AWS Cloud offers improved security, scale, and performance with cloud economics. In this session, we provide an overview of Amazon WorkSpaces and Amazon AppStream 2.0, and we discuss the use cases for each. Then, we dive deep into best practices for implementing Amazon WorkSpaces and AppStream 2.0, including how to integrate with your existing identity, security, networking, and storage solutions.
by Rohan Dubal, Software Development Engineer, AWS
One of the biggest time sinks and challenges for mobile application developers is developing, accessing, and managing all of the disparate data sources that are involved in delivering delightful, collaborative, and real-time mobile experiences for users while also enabling offline capabilities for when a user is not connected, but still wants to use the app. In this session, you be introduced to the new AWS AppSync service that speed and simplifies these tasks for developers using GraphQL to provide a data abstraction layer and easy query and update statements without having to know the details of the underlying data sources.
Achieving Business Value with AWS - AWS Online Tech TalksAmazon Web Services
Learning Objectives:
- Learn about the business benefits of moving to the AWS platform
- Learn what the commercial levers are that can help you lower your TCO on AWS
- Discover how other enterprises have used these levers
With Alexa for Business, you can deploy and manage Alexa devices in your organization. Join us in this session to learn how you can set up an Alexa-enabled conference room and integrate Alexa with your existing equipment. Learn to build Alexa skills, and voice-enable applications such as SalesForce, ServiceNow and Trello. Discover how to build private skills for your organization and deploy them to Alexa devices and users in your workplace. Come and experience Alexa for Business in action, and get some great ideas for transforming your business.
Life of a Code Change to a Tier 1 Service - AWS Online Tech TalksAmazon Web Services
Learning Objectives:
- How Amazon's software development teams release code changes
- Cultural and operational continuous delivery best practices
- About AWS Developer Tools used to implement CI/CD
Building an end to end image recognition service - Tel Aviv Summit 2018Amazon Web Services
In this session, we’ll learn how to build and deploy end to end solutions for ingesting and processing computer vision solutions, using machine learning models connected to live video streams, and getting insights such as face detection and object analysis. At the end of the session developers of all skill levels will be able to build their own deep learning powered, computer-vision applications. Attendees will learn how to experiment with different projects for face detection, object recognition and other video-based AWS Machine Learning services.
Learn how to seamlessly combine Amazon EC2 On-Demand, Spot, and Reserved Instances to optimize cost, scale, and performance. Understand best practices used by customers all over the world for the most commonly used applications and workloads. Discover multiple ways to grow your compute capacity, and enable new types of cloud computing applications—without it costing a lot of money.
Learning Objectives:
-Understand how to use a graph model and query languages to build applications over highly connected data
-Understand how the features of Amazon Neptune enable you to build production ready graph applications -Learn how to get started
Unlocking New Todays: Artificial Intelligence and Data Platforms on AWSAmazon Web Services
In this session, you will learn about our strategy for driving machine learning innovation for our customers and learn what’s new from AWS in the machine learning space. We will discuss and demonstrate the latest new services for ML on AWS: Amazon SageMaker, AWS DeepLens, Amazon Rekogntion Video, Amazon Translate, Amazon Transcribe, and Amazon Comprehend. Attend this session to understand how to make the most of machine learning in the cloud.
Anyone can create and publish augmented reality (AR), virtual reality (VR), and 3D applications quickly and easily with Amazon Sumerian. 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.
BDA304 Build Deep Learning Applications with TensorFlow and Amazon SageMakerAmazon Web Services
Deep learning continues to push the state of the art in domains such as computer vision, natural language understanding, and recommendation engines. In this session, you learn how to get started with the TensorFlow deep learning framework using Amazon SageMaker, a platform to easily build, train, and use to deploy models at scale. You learn how to build a model using TensorFlow by setting up a Jupyter Notebook to get started with image and object recognition. You also learn how to quickly train and deploy a model through Amazon SageMaker.
ATC302_How to Leverage AWS Machine Learning Services to Analyze and Optimize ...Amazon Web Services
In this session, you’ll learn how AdTech companies use AWS services like Glue, Athena, Quicksight, and EMR to analyze your Google DoubleClick Campaign Manager data at scale without the burden of infrastructure or worries about server maintenance. We’ll live-process a click stream so you can see how Machine Learning can help maximize your revenue by finding the most optimal path of a campaign and we’ll look at a real world demo from A9’s Advertising Science Team of how they use the data to build Look-alike Model in their projects.
Modern data is massive, quickly evolving, unstructured, and increasingly hard to catalog and understand from multiple consumers and applications. This presentation will guide you though the best practices for designing a robust data architecture, highlightning the benefits and typical challenges of data lakes and data warehouses. We will build a scalable solution based on managed services such as Amazon Athena, AWS Glue, and AWS Lake Formation.
Building Content Recommendation Systems Using Apache MXNet and Gluon - MCL402...Amazon Web Services
Recommendations are becoming an integral part of how many business serve customers, from targeted shopping on demand video. In this session, you’ll learn the key elements to build a recommendation system using Gluon, the new intuitive, dynamic programming interface for Apache MXNet. You’ll use matrix factorization techniques to build a video on-demand solution using deep learning.
SRV309 AWS Purpose-Built Database Strategy: The Right Tool for the Right JobAmazon Web Services
In this session, Shawn Bice, VP of NoSQL and QuickSight, covers the AWS purpose-built strategy for databases and explains why your application should drive the requirements of a database, not the other way around. We introduce AWS databases that are purpose-built for your application use cases. Learn why you should select different data services to solve different aspects of an application, and watch a demonstration on which application use cases lend themselves well to which data services. If you’re a developer building modern applications that require flexibility and consistent millisecond performance, and you’re trying to determine what relational and non-relational data services to use, this session is for you.
SRV317 Creating and Publishing AR and VR Apps with Amazon SumerianAmazon Web Services
Amazon Sumerian lets anyone create and run augmented reality (AR), virtual reality (VR), and 3D applications quickly and easily without requiring specialized programming or 3D graphics expertise. In this session, participants learn how to use Sumerian to build a scene that is viewable on laptops, mobile phones, VR headsets, and digital signage. Ben Moore provides a guided overview of the Sumerian interface to create a scene, add objects, and include hosts. He then demonstrates how to manipulate assets and add behaviors to create dynamically animated objects and characters in an AR/VR experience. Finally, he covers how Sumerian integrates into AWS services such as Amazon Polly, Amazon Lex, AWS Lambda, Amazon S3, and Amazon DynamoDB.
Big Data, Analytics and Machine Learning on AWS Lambda - SRV402 - re:Invent 2017Amazon Web Services
AWS Lambda is a great fit for many data processing tasks, for data analytics and for machine learning inference. The Lambda team use Lambda for our own Analytics in conjunction with other AWS services. In this session, we will cover how we tie these services together to crunch the data Lambda creates to generate insights to better run our service. We will cover common design patterns for big data processing, how they map to Lambda and serverless, and look at some new patterns that serverless makes possible. Finally we will look to how to leverage Machine Learning inference on Lambda to derive better insights from the data.
Move your Desktops and Apps to AWS with Amazon WorkSpaces and AppStream 2 Amazon Web Services
IT organizations today need to support a modern, flexible, global workforce and ensure that their users can be productive anywhere. Moving desktops and applications to the AWS Cloud offers improved security, scale, and performance with cloud economics. In this session, we provide an overview of Amazon WorkSpaces and Amazon AppStream 2.0, and we discuss the use cases for each. Then, we dive deep into best practices for implementing Amazon WorkSpaces and AppStream 2.0, including how to integrate with your existing identity, security, networking, and storage solutions.
by Rohan Dubal, Software Development Engineer, AWS
One of the biggest time sinks and challenges for mobile application developers is developing, accessing, and managing all of the disparate data sources that are involved in delivering delightful, collaborative, and real-time mobile experiences for users while also enabling offline capabilities for when a user is not connected, but still wants to use the app. In this session, you be introduced to the new AWS AppSync service that speed and simplifies these tasks for developers using GraphQL to provide a data abstraction layer and easy query and update statements without having to know the details of the underlying data sources.
Achieving Business Value with AWS - AWS Online Tech TalksAmazon Web Services
Learning Objectives:
- Learn about the business benefits of moving to the AWS platform
- Learn what the commercial levers are that can help you lower your TCO on AWS
- Discover how other enterprises have used these levers
With Alexa for Business, you can deploy and manage Alexa devices in your organization. Join us in this session to learn how you can set up an Alexa-enabled conference room and integrate Alexa with your existing equipment. Learn to build Alexa skills, and voice-enable applications such as SalesForce, ServiceNow and Trello. Discover how to build private skills for your organization and deploy them to Alexa devices and users in your workplace. Come and experience Alexa for Business in action, and get some great ideas for transforming your business.
Life of a Code Change to a Tier 1 Service - AWS Online Tech TalksAmazon Web Services
Learning Objectives:
- How Amazon's software development teams release code changes
- Cultural and operational continuous delivery best practices
- About AWS Developer Tools used to implement CI/CD
Building an end to end image recognition service - Tel Aviv Summit 2018Amazon Web Services
In this session, we’ll learn how to build and deploy end to end solutions for ingesting and processing computer vision solutions, using machine learning models connected to live video streams, and getting insights such as face detection and object analysis. At the end of the session developers of all skill levels will be able to build their own deep learning powered, computer-vision applications. Attendees will learn how to experiment with different projects for face detection, object recognition and other video-based AWS Machine Learning services.
Learn how to seamlessly combine Amazon EC2 On-Demand, Spot, and Reserved Instances to optimize cost, scale, and performance. Understand best practices used by customers all over the world for the most commonly used applications and workloads. Discover multiple ways to grow your compute capacity, and enable new types of cloud computing applications—without it costing a lot of money.
Learning Objectives:
-Understand how to use a graph model and query languages to build applications over highly connected data
-Understand how the features of Amazon Neptune enable you to build production ready graph applications -Learn how to get started
Unlocking New Todays: Artificial Intelligence and Data Platforms on AWSAmazon Web Services
In this session, you will learn about our strategy for driving machine learning innovation for our customers and learn what’s new from AWS in the machine learning space. We will discuss and demonstrate the latest new services for ML on AWS: Amazon SageMaker, AWS DeepLens, Amazon Rekogntion Video, Amazon Translate, Amazon Transcribe, and Amazon Comprehend. Attend this session to understand how to make the most of machine learning in the cloud.
Anyone can create and publish augmented reality (AR), virtual reality (VR), and 3D applications quickly and easily with Amazon Sumerian. 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.
BDA304 Build Deep Learning Applications with TensorFlow and Amazon SageMakerAmazon Web Services
Deep learning continues to push the state of the art in domains such as computer vision, natural language understanding, and recommendation engines. In this session, you learn how to get started with the TensorFlow deep learning framework using Amazon SageMaker, a platform to easily build, train, and use to deploy models at scale. You learn how to build a model using TensorFlow by setting up a Jupyter Notebook to get started with image and object recognition. You also learn how to quickly train and deploy a model through Amazon SageMaker.
ATC302_How to Leverage AWS Machine Learning Services to Analyze and Optimize ...Amazon Web Services
In this session, you’ll learn how AdTech companies use AWS services like Glue, Athena, Quicksight, and EMR to analyze your Google DoubleClick Campaign Manager data at scale without the burden of infrastructure or worries about server maintenance. We’ll live-process a click stream so you can see how Machine Learning can help maximize your revenue by finding the most optimal path of a campaign and we’ll look at a real world demo from A9’s Advertising Science Team of how they use the data to build Look-alike Model in their projects.
NEW LAUNCH! Introducing Amazon SageMaker - MCL365 - re:Invent 2017Amazon Web Services
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. This session will introduce you the features of Amazon SageMaker, including a one-click training environment, highly-optimized machine learning algorithms with built-in model tuning, and deployment without engineering effort. With zero-setup required, Amazon SageMaker significantly decreases your training time and overall cost of building production machine learning systems. You'll also hear how and why Intuit is using Amazon SaeMaker on AWS for real-time fraud detection.
Working with Amazon SageMaker Algorithms for Faster Model TrainingAmazon Web Services
Amazon SageMaker is a fully-managed service that enables developers and data scientists to quickly and easily build, train, and deploy machine learning (ML) models, at any scale. Amazon SageMaker provides high-performance, machine learning algorithms optimized for speed, scale, and accuracy, to perform training on petabyte-scale data sets. This webinar will introduce you to the collection of distributed streaming ML algorithms that come with Amazon SageMaker. You will learn about the difference between streaming and batch ML algorithms, and how SageMaker has been architected to run these algorithms at scale. We will demo Neural Topic Modeling of text documents using a sample SageMaker Notebook, which will be made available to attendees.
ENT212-An Overview of Best Practices for Large-Scale MigrationsAmazon Web Services
We've partnered with hundreds of customers on their large-scale migrations to AWS. This session outlines some of the common challenges that our customers face and how they've overcome these challenges. The session also describes the patterns we've observed that make legacy migrations successful, and the mechanisms we've created to help customers migrate faster.
GPSTEC201_Building an Artificial Intelligence Practice for Consulting PartnersAmazon Web Services
Companies around the world are looking at using artificial intelligence and machine learning to launch new innovative products and services and to drive efficiencies via automation in their businesses. Come to this session to understand why you should consider building an AI/ML practice in your consulting company. Learn the importance of having strong data engineering skills, including data annotation, and get some tips on building a data science team that can deliver customer projects.
Whether you’re just getting started with AI or you’re a deep learning expert, this session will provide a meaningful overview of how to get started with Artificial Intelligence on the AWS Cloud. In particular, we will explore AWS cloud-native machine learning and deep learning technologies that address a range of different use cases and needs. These include AWS Lex, which provides natural language understanding (NLU) and automatic speech recognition (ASR); Amazon Rekognition, which provides visual search and image recognition capabilities; Amazon Polly for text-to-speech (TTS) capabilities; and Amazon Machine Learning tools. The session will also cover the AWS Deep Learning AMI, which lets you run deep learning in the cloud at any scale.
If you're based in South East Asia, join us for upcoming AWS Webinar Series https://aws.amazon.com/events/asean/webinars/
In this session, learn about Amazon Connect and how your organization can benefit from its capabilities, extensibility, and scalability. We explain how it’s designed to use AWS natural language understanding to provide enterprise and consumer interactions that replicate the experiences consumers have at home with their Echo products. Learn how to combine Amazon Connect with leading CRM, analytics, and workforce optimization/quality management platforms to provide a complete system of engagement and system of record for enterprises across all verticals and size ranges.
RET304_Rapidly Respond to Demanding Retail Customers with the Same Serverless...Amazon Web Services
Today’s retail customers want to set the rules on how and when they buy, receive, and return their product. But many retailers are struggling to unify their sales channels using existing legacy e-commerce software stacks. To consistently serve customers across retail channels, retailers must adopt a modern architecture that is elastic, cost effective, and based on loosely coupled application services. In this session, we dive deep into how retailers can leverage serverless architectures using Amazon API Gateway, AWS Lambda, and Amazon DynamoDB. Learn how Amazon Fresh quickly responded to customer feedback on the Totes Pickup feature, developing a cost-effective and scalable self-service serverless application to deliver a 1-click experience for the customer, while providing faster insights back to the business.
GPSBUS215-Maximize Innovation and Agility by Building Your SAAS Solution on AWSAmazon Web Services
Partners increasingly look to a Software as a Service (SaaS) delivery model for products to respond to customer demand, improve operational efficiency, increase agility, and expand market and global reach. AWS provides a low-cost, reliable, and secure foundation to use as you build and deliver SaaS solutions to your customers. The AWS Partner Network (APN) helps you build a successful AWS-based business by providing valuable business, technical, marketing, and go-to-market (GTM) support. In this session, we discuss what a typical journey to SaaS on AWS looks like, and all of the AWS and APN resources and benefits available to you in every stage.
Keith Steward - SageMaker Algorithms Infinitely Scalable Machine Learning_VK.pdfAmazon Web Services
Amazon SageMaker is a fully-managed service that enables developers and data scientists to quickly and easily build, train, and deploy machine learning (ML) models, at any scale. Amazon SageMaker provides high-performance, machine learning algorithms optimized for speed, scale, and accuracy, to perform training on petabyte-scale data sets. This webinar will introduce you to the collection of distributed streaming ML algorithms that come with Amazon SageMaker. You will learn about the difference between streaming and batch ML algorithms, and how SageMaker has been architected to run these algorithms at scale. We will demo Neural Topic Modeling of text documents using a sample SageMaker Notebook, which will be made available to attendees.
SageMaker Algorithms Infinitely Scalable Machine LearningAmazon Web Services
Amazon SageMaker is a fully-managed service that enables developers and data scientists to quickly and easily build, train, and deploy machine learning (ML) models, at any scale. Amazon SageMaker provides high-performance, machine learning algorithms optimized for speed, scale, and accuracy, to perform training on petabyte-scale data sets. This webinar will introduce you to the collection of distributed streaming ML algorithms that come with Amazon SageMaker. You will learn about the difference between streaming and batch ML algorithms, and how SageMaker has been architected to run these algorithms at scale. We will demo Neural Topic Modeling of text documents using a sample SageMaker Notebook, which will be made available to attendees.
Level: 300-400
Speaker: Binoy Das - Partner Solutions Architect, AWS
How serverless helps startups innovate and scaleGabe Hollombe
An overview of what it means to be 'Serverless', reasons why Serverless is a good way to develop and deploy software, and examples for apps, analytics, and devops.
by Anupam Mishra, AWS Solutions Architect
For startup tech leaders, it's a balancing act: aiming to accelerate product development, while also being mindful of how rushed technology choices can introduce unnecessary business risk.
Come to this session to learn how to start releasing features faster with an entire continuous delivery toolchain deployed in minutes with AWS CodeStar. See how you can easily track progress across your product backlog until actual deployment in production. We will show you specific AWS services to use to future-proof your architecture and avoid over-engineering. Prepare for success by deploying your app on a scalable platform like Amazon Elastic Beanstalk - without a steep learning curve or complex infrastructure configuration work.
Finally leverage one of the turnkey AWS Solutions you can launch with a few clicks; a reference implementation to make data driven decisions about product roadmap using real time analytics.
Working with Amazon SageMaker Algorithms for Faster Model TrainingAmazon Web Services
Amazon SageMaker is a fully-managed service that enables developers and data scientists to quickly and easily build, train, and deploy machine learning (ML) models, at any scale. Amazon SageMaker provides high-performance, machine learning algorithms optimized for speed, scale, and accuracy, to perform training on petabyte-scale data sets. This webinar will introduce you to the collection of distributed streaming ML algorithms that come with Amazon SageMaker. You will learn about the difference between streaming and batch ML algorithms, and how SageMaker has been architected to run these algorithms at scale. We will demo Neural Topic Modeling of text documents using a sample SageMaker Notebook, which will be made available to attendees.
Building the Business of the Future: Leveraging A.I. and Machine Learning - A...Amazon Web Services
<Management Track>
Olivier Klein, Emerging Technologies Solutions Architect, Amazon Web Services
Artificial Intelligence (AI) and Machine Learning (ML) are no longer the stuff of science fiction. Organizations are increasingly using A.I. and Machine Learning to drive innovation -- namely, Amazon.com's retail experience. Join us for an inside look at how Amazon thinks about this technology, and gain insight into a range of new AI/ML services offered by AWS for use in your own business.
GPSBUS204_Building a Profitable Next Generation AWS MSP PracticeAmazon Web Services
Join us in this session to learn more about the evolving landscape for AWS Partners capable of providing a full lifecycle experience for their customers, from plan and design to build and migrate to run, operate, and optimize. We share in-depth information about the investment, revenue, and margin opportunities for these next-gen MSPs. We also dive into AWS services and third-party tooling to help partners along this journey. Partners leave this session with a clear view of new ways to optimize their AWS business, expand their customer offerings, and improve their profitability.
ABD307_Deep Analytics for Global AWS Marketing OrganizationAmazon Web Services
To meet the needs of the global marketing organization, the AWS marketing analytics team built a scalable platform that allows the data science team to deliver custom econometric and machine learning models for end user self-service. To meet data security standards, we use end-to-end data encryption and different AWS services such as Amazon Redshift, Amazon RDS, Amazon S3, Amazon EMR with Apache Spark and Auto Scaling. In this session, you see real examples of how we have scaled and automated critical analysis, such as calculating the impact of marketing programs like re:Invent and prioritizing leads for our sales teams.
Come costruire servizi di Forecasting sfruttando algoritmi di ML e deep learn...Amazon Web Services
Il Forecasting è un processo importante per tantissime aziende e viene utilizzato in vari ambiti per cercare di prevedere in modo accurato la crescita e distribuzione di un prodotto, l’utilizzo delle risorse necessarie nelle linee produttive, presentazioni finanziarie e tanto altro. Amazon utilizza delle tecniche avanzate di forecasting, in parte questi servizi sono stati messi a disposizione di tutti i clienti AWS.
In questa sessione illustreremo come pre-processare i dati che contengono una componente temporale e successivamente utilizzare un algoritmo che a partire dal tipo di dato analizzato produce un forecasting accurato.
Big Data per le Startup: come creare applicazioni Big Data in modalità Server...Amazon Web Services
La varietà e la quantità di dati che si crea ogni giorno accelera sempre più velocemente e rappresenta una opportunità irripetibile per innovare e creare nuove startup.
Tuttavia gestire grandi quantità di dati può apparire complesso: creare cluster Big Data su larga scala sembra essere un investimento accessibile solo ad aziende consolidate. Ma l’elasticità del Cloud e, in particolare, i servizi Serverless ci permettono di rompere questi limiti.
Vediamo quindi come è possibile sviluppare applicazioni Big Data rapidamente, senza preoccuparci dell’infrastruttura, ma dedicando tutte le risorse allo sviluppo delle nostre le nostre idee per creare prodotti innovativi.
Ora puoi utilizzare Amazon Elastic Kubernetes Service (EKS) per eseguire pod Kubernetes su AWS Fargate, il motore di elaborazione serverless creato per container su AWS. Questo rende più semplice che mai costruire ed eseguire le tue applicazioni Kubernetes nel cloud AWS.In questa sessione presenteremo le caratteristiche principali del servizio e come distribuire la tua applicazione in pochi passaggi
Vent'anni fa Amazon ha attraversato una trasformazione radicale con l'obiettivo di aumentare il ritmo dell'innovazione. In questo periodo abbiamo imparato come cambiare il nostro approccio allo sviluppo delle applicazioni ci ha permesso di aumentare notevolmente l'agilità, la velocità di rilascio e, in definitiva, ci ha consentito di creare applicazioni più affidabili e scalabili. In questa sessione illustreremo come definiamo le applicazioni moderne e come la creazione di app moderne influisce non solo sull'architettura dell'applicazione, ma sulla struttura organizzativa, sulle pipeline di rilascio dello sviluppo e persino sul modello operativo. Descriveremo anche approcci comuni alla modernizzazione, compreso l'approccio utilizzato dalla stessa Amazon.com.
Come spendere fino al 90% in meno con i container e le istanze spot Amazon Web Services
L’utilizzo dei container è in continua crescita.
Se correttamente disegnate, le applicazioni basate su Container sono molto spesso stateless e flessibili.
I servizi AWS ECS, EKS e Kubernetes su EC2 possono sfruttare le istanze Spot, portando ad un risparmio medio del 70% rispetto alle istanze On Demand. In questa sessione scopriremo insieme quali sono le caratteristiche delle istanze Spot e come possono essere utilizzate facilmente su AWS. Impareremo inoltre come Spreaker sfrutta le istanze spot per eseguire applicazioni di diverso tipo, in produzione, ad una frazione del costo on-demand!
In recent months, many customers have been asking us the question – how to monetise Open APIs, simplify Fintech integrations and accelerate adoption of various Open Banking business models. Therefore, AWS and FinConecta would like to invite you to Open Finance marketplace presentation on October 20th.
Event Agenda :
Open banking so far (short recap)
• PSD2, OB UK, OB Australia, OB LATAM, OB Israel
Intro to Open Finance marketplace
• Scope
• Features
• Tech overview and Demo
The role of the Cloud
The Future of APIs
• Complying with regulation
• Monetizing data / APIs
• Business models
• Time to market
One platform for all: a Strategic approach
Q&A
Rendi unica l’offerta della tua startup sul mercato con i servizi Machine Lea...Amazon Web Services
Per creare valore e costruire una propria offerta differenziante e riconoscibile, le startup di successo sanno come combinare tecnologie consolidate con componenti innovativi creati ad hoc.
AWS fornisce servizi pronti all'utilizzo e, allo stesso tempo, permette di personalizzare e creare gli elementi differenzianti della propria offerta.
Concentrandoci sulle tecnologie di Machine Learning, vedremo come selezionare i servizi di intelligenza artificiale offerti da AWS e, anche attraverso una demo, come costruire modelli di Machine Learning personalizzati utilizzando SageMaker Studio.
OpsWorks Configuration Management: automatizza la gestione e i deployment del...Amazon Web Services
Con l'approccio tradizionale al mondo IT per molti anni è stato difficile implementare tecniche di DevOps, che finora spesso hanno previsto attività manuali portando di tanto in tanto a dei downtime degli applicativi interrompendo l'operatività dell'utente. Con l'avvento del cloud, le tecniche di DevOps sono ormai a portata di tutti a basso costo per qualsiasi genere di workload, garantendo maggiore affidabilità del sistema e risultando in dei significativi miglioramenti della business continuity.
AWS mette a disposizione AWS OpsWork come strumento di Configuration Management che mira ad automatizzare e semplificare la gestione e i deployment delle istanze EC2 per mezzo di workload Chef e Puppet.
Scopri come sfruttare AWS OpsWork a garanzia e affidabilità del tuo applicativo installato su Instanze EC2.
Microsoft Active Directory su AWS per supportare i tuoi Windows WorkloadsAmazon Web Services
Vuoi conoscere le opzioni per eseguire Microsoft Active Directory su AWS? Quando si spostano carichi di lavoro Microsoft in AWS, è importante considerare come distribuire Microsoft Active Directory per supportare la gestione, l'autenticazione e l'autorizzazione dei criteri di gruppo. In questa sessione, discuteremo le opzioni per la distribuzione di Microsoft Active Directory su AWS, incluso AWS Directory Service per Microsoft Active Directory e la distribuzione di Active Directory su Windows su Amazon Elastic Compute Cloud (Amazon EC2). Trattiamo argomenti quali l'integrazione del tuo ambiente Microsoft Active Directory locale nel cloud e l'utilizzo di applicazioni SaaS, come Office 365, con AWS Single Sign-On.
Dal riconoscimento facciale al riconoscimento di frodi o difetti di fabbricazione, l'analisi di immagini e video che sfruttano tecniche di intelligenza artificiale, si stanno evolvendo e raffinando a ritmi elevati. In questo webinar esploreremo le possibilità messe a disposizione dai servizi AWS per applicare lo stato dell'arte delle tecniche di computer vision a scenari reali.
Amazon Web Services e VMware organizzano un evento virtuale gratuito il prossimo mercoledì 14 Ottobre dalle 12:00 alle 13:00 dedicato a VMware Cloud ™ on AWS, il servizio on demand che consente di eseguire applicazioni in ambienti cloud basati su VMware vSphere® e di accedere ad una vasta gamma di servizi AWS, sfruttando a pieno le potenzialità del cloud AWS e tutelando gli investimenti VMware esistenti.
Molte organizzazioni sfruttano i vantaggi del cloud migrando i propri carichi di lavoro Oracle e assicurandosi notevoli vantaggi in termini di agilità ed efficienza dei costi.
La migrazione di questi carichi di lavoro, può creare complessità durante la modernizzazione e il refactoring delle applicazioni e a questo si possono aggiungere rischi di prestazione che possono essere introdotti quando si spostano le applicazioni dai data center locali.
Crea la tua prima serverless ledger-based app con QLDB e NodeJSAmazon Web Services
Molte aziende oggi, costruiscono applicazioni con funzionalità di tipo ledger ad esempio per verificare lo storico di accrediti o addebiti nelle transazioni bancarie o ancora per tenere traccia del flusso supply chain dei propri prodotti.
Alla base di queste soluzioni ci sono i database ledger che permettono di avere un log delle transazioni trasparente, immutabile e crittograficamente verificabile, ma sono strumenti complessi e onerosi da gestire.
Amazon QLDB elimina la necessità di costruire sistemi personalizzati e complessi fornendo un database ledger serverless completamente gestito.
In questa sessione scopriremo come realizzare un'applicazione serverless completa che utilizzi le funzionalità di QLDB.
Con l’ascesa delle architetture di microservizi e delle ricche applicazioni mobili e Web, le API sono più importanti che mai per offrire agli utenti finali una user experience eccezionale. In questa sessione impareremo come affrontare le moderne sfide di progettazione delle API con GraphQL, un linguaggio di query API open source utilizzato da Facebook, Amazon e altro e come utilizzare AWS AppSync, un servizio GraphQL serverless gestito su AWS. Approfondiremo diversi scenari, comprendendo come AppSync può aiutare a risolvere questi casi d’uso creando API moderne con funzionalità di aggiornamento dati in tempo reale e offline.
Inoltre, impareremo come Sky Italia utilizza AWS AppSync per fornire aggiornamenti sportivi in tempo reale agli utenti del proprio portale web.
Database Oracle e VMware Cloud™ on AWS: i miti da sfatareAmazon Web Services
Molte organizzazioni sfruttano i vantaggi del cloud migrando i propri carichi di lavoro Oracle e assicurandosi notevoli vantaggi in termini di agilità ed efficienza dei costi.
La migrazione di questi carichi di lavoro, può creare complessità durante la modernizzazione e il refactoring delle applicazioni e a questo si possono aggiungere rischi di prestazione che possono essere introdotti quando si spostano le applicazioni dai data center locali.
In queste slide, gli esperti AWS e VMware presentano semplici e pratici accorgimenti per facilitare e semplificare la migrazione dei carichi di lavoro Oracle accelerando la trasformazione verso il cloud, approfondiranno l’architettura e dimostreranno come sfruttare a pieno le potenzialità di VMware Cloud ™ on AWS.
Amazon Elastic Container Service (Amazon ECS) è un servizio di gestione dei container altamente scalabile, che semplifica la gestione dei contenitori Docker attraverso un layer di orchestrazione per il controllo del deployment e del relativo lifecycle. In questa sessione presenteremo le principali caratteristiche del servizio, le architetture di riferimento per i differenti carichi di lavoro e i semplici passi necessari per poter velocemente migrare uno o più dei tuo container.