Internet of Things is creating a tidal wave of new data including events, correlations, business value, and much more. With the proliferation of new data sets, it also introduces more potential issues, errors, and spurious values.
In this session, we will explore using Amazon Machine Learning to analyse and understand the new data collected within your IoT solution. In addition, we will learn how to discover patterns, trends, anomalies, and correlations by demonstrating the capabilities of Amazon Machine Learning and SparkML running on AWS Cloud.
Speaker: Simon Elisha, Solutions Architect, Amazon Web Services
Mobile Apps are increasingly popular these days to deliver efficient and cost-effective ways to interact with your end consumers. Amazon Web Services offers a number of services that help you to easily launch apps in the cloud, scale them cost-effectively and deliver them to your global customer base. This session will cover our native mobile app services like AWS Mobile Analytics, Amazon Cognito, Amazon SNS or AWS Device Farm, including the SDKs for iOS and Android. It will also demonstrate how to create fully managed and scalable applications using AWS Lambda, our new compute service that runs your code in response to events and manages compute resources for you, in conjunction with Amazon API Gateway that acts as a “front door” for applications to access data, business logic, or functionality from your back-end services. Lastly, it will cover how the new AWS Mobile Hub can help you develop your mobile apps even faster.
Olivier Klein, Solutions Architect, Amazon Web Services, Greater China
Alex Coqueiro, Senior Solutions Architect Manager for Latin America and Canada, takes us on a journey into machine learning, IoT and the AWS cloud. In this presentation/demo, he shows us what's possible - integrate voice command, IoT, Lambda functions, voice synthesis - learn the Art of Possible with the AWS Cloud.
Legacy monitoring and troubleshooting tools can limit visibility and control over your infrastructure and applications. Organizations must find monitoring and troubleshooting tools that can scale with the volume, variety and velocity of data generated by today’s complex applications in order to keep pace with business demands. Our upcoming webinar will discuss how Sumo Logic helped Scripps Networks harness cloud-native machine data analytics to improve application quality and reliability on AWS. Sumo Logic allows IT operations teams to visualize and monitor workloads in real-time, identify issues and expedite root-cause analysis across the AWS environment.
Join us to learn:
• How to migrate from traditional on-premises data centers to AWS with confidence
• How to improve the monitoring and troubleshooting of modern applications
• How Scripps Networks, a leading content developer, used Sumo Logic to optimize their transition to AWS
Who should attend: Developers, DevOps Director/Manager, IT Operations Director/Manager, Director of Cloud/Infrastructure, VP of Engineering
Next Generation Education: Technology in the Classroom and BeyondAmazon Web Services
The implementation of highly scalable, easy-to-deploy technology is radically transforming educational models and student engagement. For education, the cloud offers not only cost savings and agility, but the opportunity to develop breakthroughs in research, accelerate learning, enhance educational models, and increase student engagement. The “always-up, always-on" infrastructure supports next generation education. Learn the practical strategies being deployed by venerable universities and startup educational technology companies for breaking down barriers to delivering content, accessing information, and overcoming economics to meet students where they are. This session will highlight how cloud can accelerate breakthroughs in educational models and learning outcomes by providing on-demand access to powerful computing.
Vincent Quah, Business Development Lead for the Education, Research and Not For Profit , Amazon Web Services, WWPS APJ
Legacy on-premises identity and access management (IAM) solutions can slow your organization’s efficiency by forcing employees to focus on administrative tasks rather than business needs. Your organization can benefit from a tool to streamline IAM on AWS that securely connects users and ensures appropriate access to resources. Okta is an integrated identity and mobility management service. Learn through customer use cases how Okta has helped various organizations connect employees to the cloud by leveraging services such as AWS Identity and Access Management (AWS IAM) and logging services like AWS CloudTrail.
Join us to learn:
• Best practices for overcoming IAM challenges in the cloud, such as accessing multiple applications across multiple domains and securing your mobile workforce
• How to authenticate, manage, and secure your users’ access to the AWS Cloud more easily with Okta on AWS
• How to streamline identity management and the associated administrative tasks
Who should attend: IT Manager, IT Security Manager, Solution Architect, Cloud App Architect, Product Management, Product Manager, Business Development
Andy Jassy Illuminates Amazon Web ServicesMichael Skok
Andy Jassy, senior vice president of Amazon Web Services, provides an overview of AWS at the May 8, 2013 Startup Secrets session at Harvard innovation lab.
Mobile Apps are increasingly popular these days to deliver efficient and cost-effective ways to interact with your end consumers. Amazon Web Services offers a number of services that help you to easily launch apps in the cloud, scale them cost-effectively and deliver them to your global customer base. This session will cover our native mobile app services like AWS Mobile Analytics, Amazon Cognito, Amazon SNS or AWS Device Farm, including the SDKs for iOS and Android. It will also demonstrate how to create fully managed and scalable applications using AWS Lambda, our new compute service that runs your code in response to events and manages compute resources for you, in conjunction with Amazon API Gateway that acts as a “front door” for applications to access data, business logic, or functionality from your back-end services. Lastly, it will cover how the new AWS Mobile Hub can help you develop your mobile apps even faster.
Olivier Klein, Solutions Architect, Amazon Web Services, Greater China
Alex Coqueiro, Senior Solutions Architect Manager for Latin America and Canada, takes us on a journey into machine learning, IoT and the AWS cloud. In this presentation/demo, he shows us what's possible - integrate voice command, IoT, Lambda functions, voice synthesis - learn the Art of Possible with the AWS Cloud.
Legacy monitoring and troubleshooting tools can limit visibility and control over your infrastructure and applications. Organizations must find monitoring and troubleshooting tools that can scale with the volume, variety and velocity of data generated by today’s complex applications in order to keep pace with business demands. Our upcoming webinar will discuss how Sumo Logic helped Scripps Networks harness cloud-native machine data analytics to improve application quality and reliability on AWS. Sumo Logic allows IT operations teams to visualize and monitor workloads in real-time, identify issues and expedite root-cause analysis across the AWS environment.
Join us to learn:
• How to migrate from traditional on-premises data centers to AWS with confidence
• How to improve the monitoring and troubleshooting of modern applications
• How Scripps Networks, a leading content developer, used Sumo Logic to optimize their transition to AWS
Who should attend: Developers, DevOps Director/Manager, IT Operations Director/Manager, Director of Cloud/Infrastructure, VP of Engineering
Next Generation Education: Technology in the Classroom and BeyondAmazon Web Services
The implementation of highly scalable, easy-to-deploy technology is radically transforming educational models and student engagement. For education, the cloud offers not only cost savings and agility, but the opportunity to develop breakthroughs in research, accelerate learning, enhance educational models, and increase student engagement. The “always-up, always-on" infrastructure supports next generation education. Learn the practical strategies being deployed by venerable universities and startup educational technology companies for breaking down barriers to delivering content, accessing information, and overcoming economics to meet students where they are. This session will highlight how cloud can accelerate breakthroughs in educational models and learning outcomes by providing on-demand access to powerful computing.
Vincent Quah, Business Development Lead for the Education, Research and Not For Profit , Amazon Web Services, WWPS APJ
Legacy on-premises identity and access management (IAM) solutions can slow your organization’s efficiency by forcing employees to focus on administrative tasks rather than business needs. Your organization can benefit from a tool to streamline IAM on AWS that securely connects users and ensures appropriate access to resources. Okta is an integrated identity and mobility management service. Learn through customer use cases how Okta has helped various organizations connect employees to the cloud by leveraging services such as AWS Identity and Access Management (AWS IAM) and logging services like AWS CloudTrail.
Join us to learn:
• Best practices for overcoming IAM challenges in the cloud, such as accessing multiple applications across multiple domains and securing your mobile workforce
• How to authenticate, manage, and secure your users’ access to the AWS Cloud more easily with Okta on AWS
• How to streamline identity management and the associated administrative tasks
Who should attend: IT Manager, IT Security Manager, Solution Architect, Cloud App Architect, Product Management, Product Manager, Business Development
Andy Jassy Illuminates Amazon Web ServicesMichael Skok
Andy Jassy, senior vice president of Amazon Web Services, provides an overview of AWS at the May 8, 2013 Startup Secrets session at Harvard innovation lab.
From my session at DevTernity in Riga, December 1st 2015. Have you always wanted to add predictive capabilities to your application, but haven’t been able to find the time or the right technology to get started? Everybody wants to build smart apps, but only a few are Data Scientists. We had the same issue inside Amazon, so we created a Machine Learning engine that Developers can easily use. The same approach is now available in the AWS cloud. We demonstrate how to use Amazon Machine Learning (Amazon ML) to create machine learning models, deploy them to production, and obtain predictions in real-time. We then demonstrate how to build a complete smart application using Amazon ML, Amazon Kinesis, and AWS Lambda. We walk you through the process flow and architecture, demonstrate outcomes, and then dive into the implementation. In this session, you learn how to use Amazon ML as well as how to integrate Amazon ML into your applications to take advantage of predictive analysis in the cloud.
Build a Recommendation Engine using Amazon Machine Learning in Real-timeAmazon Web Services
Amazon Machine Learning is a service that makes it easy for developers of all skill levels to use machine learning technology. In this session, we will introduce how to use Amazon Machine Learning to create a data model, and use it to generate the real-time prediction for your application.
Governments around the world are taking advantage of cloud not only to reduce costs, but to transform the way they deliver on their mission. The expectations of an increasingly digital citizenry are high, yet all levels of government are facing budgetary and human resource constraints. Cloud computing (on-demand delivery of IT resources via the Internet with pay-as-you-go pricing) can help government organizations increase innovation, agility, and resiliency; all while reducing costs. The session will highlight the transformative impact of cloud architectures, practical strategies being deployed by governments worldwide to break down innovation barriers, and tackle mission-critical operations with the cloud.
Peter Moore, Regional Managing Director, Amazon Web Services, WWPS APJ
Application developers need to deal with an ever growing volume of streaming data and the challenges of processing that data on a near real-time basis . This session will cover how AWS services such as Amazon Kinesis Streams, Firehose and Analytics, AWS IoT, AWS Lambda, AWS API Gateway and Amazon SNS can be used in a developer centric context to ingest, transform, process and visualise streaming data using serverless architectures.
Speakers:
Marc Teichtahl, Manager Solutions Architect, Amazon Web Services
Daniel Zoltak, Solutions Architect, Amazon Web Services
Mobile app development can be complex and time-consuming. Learn how to rapidly deliver mobile apps with AWS Mobile Hub. We will demonstrate how AWS Mobile Hub abstracts the undifferentiated heavy lifting by providing a single, integrated experience for discovering, provisioning and configuring AWS cloud resources you need to build, test, and monitor usage of your mobile apps.
Working with big volumes of data is a complicated task, but it's even harder if you have to do everything in real time and try to figure it all out yourself. Over the past decades many open-source projects helped solve problems within the data analytics lifecycle around ingestion, storage, processing and visualisation of data. This session will use practical examples to discuss architectural best practices and lessons learned when solving real-time analytics and data visualisation decision-making problems with open-source at scale with the power of Amazon Web Services. It furthermore dives into a demo, using source code from the AWS Labs to visualise live data streams at scale.
Olivier Klein, Solutions Architect, Amazon Web Services, Greater China
One Click Enterprise IoT Services - March 2017 AWS Online Tech TalksAmazon Web Services
The AWS IoT Button is a programmable button based on the Amazon Dash Button hardware offering a one-click experience for users to access applications in the cloud. Enterprises can build fully customized IoT applications, or select from a list of predefined “blueprints” to provide innovative experiences to their consumers, simplify their customer interface, and increase engagement and brand loyalty. In this webinar, we will explain why the AWS IoT Button is the simplest way to get started with IoT and discuss how you can develop applications in the cloud that are activated by one click of the button.
Learning Objectives:
- Learn how to get started with IoT using the AWS IoT Button
- Learn how to leverage the AWS IoT Button to increase customer engagement
- Learn how other AWS customers have used the AWS IoT button to build new experiences
Amazon EC2 provides a broad selection of instance types to accommodate a diverse mix of workloads. In this session, we provide an overview of the Amazon EC2 instance platform, key features, and the concept of instance generations.
Bringing the Internet of Things “IoT” to Government: Enabling Smart NationsAmazon Web Services
Local and regional governments around the world are using the cloud to transform services, improve their operations, and reach new horizons for citizen services. People are more connected to each other than ever before, and the increased connectivity of devices creates new opportunities for the public sector to truly become hubs of innovation, driving technology solutions to help improve citizens' lives. This session highlights how AWS IoT enables applications to communicate with all of your devices, all the time, even when they aren’t connected, with the goal of driving cost savings, innovation, and enhanced decision making for smarter cities. You will learn how governments are accessing the data generated from IoT applications for innovation in areas such as improved citizen requests and service delivery across government.
Mark Ryland, Chief Solutions Architect, Amazon Web Services, WWPS
AWS October Webinar Series - Getting Started with AWS IoTAmazon Web Services
AWS IoT is a managed cloud platform that lets connected devices easily and securely interact with cloud applications and other devices.
In this webinar, we will discuss how constrained devices can leverage AWS IoT to send data to the cloud and receive commands back to the device from the cloud using protocol of their choice. We will discuss how devices can securely connect using MQTT and HTTP protocols, and how developers and businesses can leverage features of AWS IoT like Thing Shadows and Rules Engine to build a real connected product.
Learn what are the challenges to embrace big data and how AWS enables your organisation to resolve challenges and leverage Big Data for Digital Transformation and innovation.
With the AWS Cloud, the city of Chicago was able to launch OpenGrid, a first-of-its-kind, open data website and mobile app that city residents can use to search for useful information and events around them ranging from real-time weather, Tweets and requests for city services to street closures, transit data and potholes nearby. This session will feature Tom Schenk, the City of Chicago’s Chief Data Officer to share their story.
An introductory session on Internet of Things (IoT) to understand how to extract more value from your connected devices. During the session, we’ll look at AWS IoT-specific services, such as AWS Greengrass and AWS IoT.
In particular, we’ll explain how they help you collect and send data from your connected devices to the cloud, analyse it and use it to manage your devices better. With less time spent collecting, loading and analysing data, you can focus on high-value projects. As part of the session, you will hear real industry examples, including a presentation from Intel on specific Intel IoT technologies, such as the Intel Developer Kit, and a case study that shows how Rio Tinto is using IoT to improve its operations. The session will also give you practical steps for getting started with IoT prototyping yourself. Speakers: Ian Massingham, AWS Evangelist and Scott Mordue, Intel IoT Developer Enabling Manager
Stream Data Analytics with Amazon Kinesis Firehose & Redshift - AWS August We...Amazon Web Services
Evolving your analytics from batch processing to real-time processing can have a major business impact, but ingesting streaming data into your data warehouse requires building complex streaming data pipelines. Amazon Kinesis Firehose solves this problem by making it easy to ingest streaming data into Amazon Redshift so that you can use existing analytics and business intelligence tools to extract information in near real-time and respond promptly. In this webinar, we will dive deep using Amazon Kinesis Firehose to load streaming data into Amazon Redshift reliably, scalably, and cost-effectively. Join us to: - Understand the basics of ingesting streaming data from sources such as mobile devices, servers, and websites with Amazon Kinesis Firehose - Get a closer look at how to automate delivery of streaming data to Amazon Redshift reliably using Amazon Kinesis Firehose - Learn techniques to detect, troubleshoot, and avoid data loading problems Who should attend: Developers, data analysts, data engineers, architects
From my session at DevTernity in Riga, December 1st 2015. Have you always wanted to add predictive capabilities to your application, but haven’t been able to find the time or the right technology to get started? Everybody wants to build smart apps, but only a few are Data Scientists. We had the same issue inside Amazon, so we created a Machine Learning engine that Developers can easily use. The same approach is now available in the AWS cloud. We demonstrate how to use Amazon Machine Learning (Amazon ML) to create machine learning models, deploy them to production, and obtain predictions in real-time. We then demonstrate how to build a complete smart application using Amazon ML, Amazon Kinesis, and AWS Lambda. We walk you through the process flow and architecture, demonstrate outcomes, and then dive into the implementation. In this session, you learn how to use Amazon ML as well as how to integrate Amazon ML into your applications to take advantage of predictive analysis in the cloud.
Build a Recommendation Engine using Amazon Machine Learning in Real-timeAmazon Web Services
Amazon Machine Learning is a service that makes it easy for developers of all skill levels to use machine learning technology. In this session, we will introduce how to use Amazon Machine Learning to create a data model, and use it to generate the real-time prediction for your application.
Governments around the world are taking advantage of cloud not only to reduce costs, but to transform the way they deliver on their mission. The expectations of an increasingly digital citizenry are high, yet all levels of government are facing budgetary and human resource constraints. Cloud computing (on-demand delivery of IT resources via the Internet with pay-as-you-go pricing) can help government organizations increase innovation, agility, and resiliency; all while reducing costs. The session will highlight the transformative impact of cloud architectures, practical strategies being deployed by governments worldwide to break down innovation barriers, and tackle mission-critical operations with the cloud.
Peter Moore, Regional Managing Director, Amazon Web Services, WWPS APJ
Application developers need to deal with an ever growing volume of streaming data and the challenges of processing that data on a near real-time basis . This session will cover how AWS services such as Amazon Kinesis Streams, Firehose and Analytics, AWS IoT, AWS Lambda, AWS API Gateway and Amazon SNS can be used in a developer centric context to ingest, transform, process and visualise streaming data using serverless architectures.
Speakers:
Marc Teichtahl, Manager Solutions Architect, Amazon Web Services
Daniel Zoltak, Solutions Architect, Amazon Web Services
Mobile app development can be complex and time-consuming. Learn how to rapidly deliver mobile apps with AWS Mobile Hub. We will demonstrate how AWS Mobile Hub abstracts the undifferentiated heavy lifting by providing a single, integrated experience for discovering, provisioning and configuring AWS cloud resources you need to build, test, and monitor usage of your mobile apps.
Working with big volumes of data is a complicated task, but it's even harder if you have to do everything in real time and try to figure it all out yourself. Over the past decades many open-source projects helped solve problems within the data analytics lifecycle around ingestion, storage, processing and visualisation of data. This session will use practical examples to discuss architectural best practices and lessons learned when solving real-time analytics and data visualisation decision-making problems with open-source at scale with the power of Amazon Web Services. It furthermore dives into a demo, using source code from the AWS Labs to visualise live data streams at scale.
Olivier Klein, Solutions Architect, Amazon Web Services, Greater China
One Click Enterprise IoT Services - March 2017 AWS Online Tech TalksAmazon Web Services
The AWS IoT Button is a programmable button based on the Amazon Dash Button hardware offering a one-click experience for users to access applications in the cloud. Enterprises can build fully customized IoT applications, or select from a list of predefined “blueprints” to provide innovative experiences to their consumers, simplify their customer interface, and increase engagement and brand loyalty. In this webinar, we will explain why the AWS IoT Button is the simplest way to get started with IoT and discuss how you can develop applications in the cloud that are activated by one click of the button.
Learning Objectives:
- Learn how to get started with IoT using the AWS IoT Button
- Learn how to leverage the AWS IoT Button to increase customer engagement
- Learn how other AWS customers have used the AWS IoT button to build new experiences
Amazon EC2 provides a broad selection of instance types to accommodate a diverse mix of workloads. In this session, we provide an overview of the Amazon EC2 instance platform, key features, and the concept of instance generations.
Bringing the Internet of Things “IoT” to Government: Enabling Smart NationsAmazon Web Services
Local and regional governments around the world are using the cloud to transform services, improve their operations, and reach new horizons for citizen services. People are more connected to each other than ever before, and the increased connectivity of devices creates new opportunities for the public sector to truly become hubs of innovation, driving technology solutions to help improve citizens' lives. This session highlights how AWS IoT enables applications to communicate with all of your devices, all the time, even when they aren’t connected, with the goal of driving cost savings, innovation, and enhanced decision making for smarter cities. You will learn how governments are accessing the data generated from IoT applications for innovation in areas such as improved citizen requests and service delivery across government.
Mark Ryland, Chief Solutions Architect, Amazon Web Services, WWPS
AWS October Webinar Series - Getting Started with AWS IoTAmazon Web Services
AWS IoT is a managed cloud platform that lets connected devices easily and securely interact with cloud applications and other devices.
In this webinar, we will discuss how constrained devices can leverage AWS IoT to send data to the cloud and receive commands back to the device from the cloud using protocol of their choice. We will discuss how devices can securely connect using MQTT and HTTP protocols, and how developers and businesses can leverage features of AWS IoT like Thing Shadows and Rules Engine to build a real connected product.
Learn what are the challenges to embrace big data and how AWS enables your organisation to resolve challenges and leverage Big Data for Digital Transformation and innovation.
With the AWS Cloud, the city of Chicago was able to launch OpenGrid, a first-of-its-kind, open data website and mobile app that city residents can use to search for useful information and events around them ranging from real-time weather, Tweets and requests for city services to street closures, transit data and potholes nearby. This session will feature Tom Schenk, the City of Chicago’s Chief Data Officer to share their story.
An introductory session on Internet of Things (IoT) to understand how to extract more value from your connected devices. During the session, we’ll look at AWS IoT-specific services, such as AWS Greengrass and AWS IoT.
In particular, we’ll explain how they help you collect and send data from your connected devices to the cloud, analyse it and use it to manage your devices better. With less time spent collecting, loading and analysing data, you can focus on high-value projects. As part of the session, you will hear real industry examples, including a presentation from Intel on specific Intel IoT technologies, such as the Intel Developer Kit, and a case study that shows how Rio Tinto is using IoT to improve its operations. The session will also give you practical steps for getting started with IoT prototyping yourself. Speakers: Ian Massingham, AWS Evangelist and Scott Mordue, Intel IoT Developer Enabling Manager
Stream Data Analytics with Amazon Kinesis Firehose & Redshift - AWS August We...Amazon Web Services
Evolving your analytics from batch processing to real-time processing can have a major business impact, but ingesting streaming data into your data warehouse requires building complex streaming data pipelines. Amazon Kinesis Firehose solves this problem by making it easy to ingest streaming data into Amazon Redshift so that you can use existing analytics and business intelligence tools to extract information in near real-time and respond promptly. In this webinar, we will dive deep using Amazon Kinesis Firehose to load streaming data into Amazon Redshift reliably, scalably, and cost-effectively. Join us to: - Understand the basics of ingesting streaming data from sources such as mobile devices, servers, and websites with Amazon Kinesis Firehose - Get a closer look at how to automate delivery of streaming data to Amazon Redshift reliably using Amazon Kinesis Firehose - Learn techniques to detect, troubleshoot, and avoid data loading problems Who should attend: Developers, data analysts, data engineers, architects
AWS re:Invent 2016: Fraud Detection with Amazon Machine Learning on AWS (FIN301)Amazon Web Services
In this session, we provide programmatic guidance on building tools and applications to detect and manage fraud and unusual activity specific to financial services institutions. Payment fraud is an ongoing concern for merchants and credit card issuers alike and these activities impact all industries, but are specifically detrimental to Financial Services. We provide a step-by-step walkthrough of a reference solution to detect and address credit card fraud in real time by using Apache Apex and Amazon Machine Learning capabilities. We also outline different resource and performance optimization options and how to work data security into the fraud detection workflow.
Data Science Popup Austin: Applied Machine Learning for IOT Domino Data Lab
Watch talk ➟ http://bit.ly/1NJLyCN
The Internet of Things is all about the data. By 2018 it is expected that the number of connect things will exceed the combined number of personal computers, smartphones, and tablets. Each ’thing’ can produce a tremendous stream of data from sensors and other sources. A short presentation will be done on some recent applications of Machine Learning, using H2O's Spark solution Sparkling Water, to the domain of data-driven machine prognostics & health management (PHM).
What Is Machine Learning?
Where do we deploy machine learning and what software and cloud services are out there to support it?
What are the trends in deploying these systems and what are the benefits for IT?
Do you have a IoT Machine Learning Case Study in the Cloud?
Amazon Machine Learning is a service that makes it easy for developers of all skill levels to use machine learning technology. In this session, we will introduce how to use S3 as a Data Lake to collect device information via AWS IoT, and then generate prediction for your application.
IoT and machine learning - Computational Intelligence conferenceAjit Jaokar
Slides for IoT and Machine learning talk. Sign up at Sign up at www.futuretext.com to get forthcoming copies of papers on IoT and Machine learning, Real time algorithms for IoT and Machine learning algorithms for Smart cities
Webinar - Comparative Analysis of Cloud based Machine Learning PlatformsBigDataCloud
This webinar discusses cloud based Machine Learning platforms in detail while identifying suitable business use cases for each of them: Microsoft Azure ML, Amazon Machine Learning DataBricks Cloud
Building prediction models with Amazon Redshift and Amazon Machine Learning -...Amazon Web Services
Mining data with Redshift, using this data to build a prediction model with Amazon ML, performing batch predictions & real-time predictions (with a Java app).
In this session we will bring some clarity to the increasingly complex big data landscape and look at the common patterns for the ingest, storage, processing, and analysis of different types of data on the AWS platform.
Speaker: Russell Nash, Solutions Architect, Amazon Web Services
Featured Customer - TechnologyOne
Have you always wanted to add predictive capabilities to your application, but haven’t been able to find the time or the right technology to get started? Everybody wants to build smart apps, but only a few are Data Scientists. We had the same issue inside Amazon, so we created a Machine Learning engine that Developers can easily use. The same approach is now available in the AWS cloud. We demonstrate how to use Amazon Machine Learning (Amazon ML) to create machine learning models, deploy them to production, and obtain predictions in real-time. We then demonstrate how to build a complete smart application using Amazon ML, Amazon Kinesis, and AWS Lambda. We walk you through the process flow and architecture, demonstrate outcomes, and then dive into the implementation. In this session, you learn how to use Amazon ML as well as how to integrate Amazon ML into your applications to take advantage of predictive analysis in the cloud.
Join us for a series of introductory and technical sessions on AWS Big Data solutions. Gain a thorough understanding of what Amazon Web Services offers across the big data lifecycle and learn architectural best practices for applying those solutions to your projects.
We will kick off this technical seminar in the morning with an introduction to the AWS Big Data platform, including a discussion of popular use cases and reference architectures. In the afternoon, we will deep dive into Machine Learning and Streaming Analytics. We will then walk everyone through building your first Big Data application with AWS.
App Dev in the Cloud: Not my circus, not my monkeys...Eric D. Schabell
When faced with all the hype around Cloud, most application developers are not really all that excited. Maybe you get that feeling that it isn't your problem, just leave me to my applications. Let me show you why, as an application developer, you can't ignore your Cloud stack anymore.
We will examine your Cloud stack anxieties and provide you with a solutions to ease you into your first private PaaS on your own local machine that you can install in just minutes. Finally you will be given a myriad of examples to take home with you to take control of this circus and own the monkeys!
http://www.schabell.org/2016/12/codemotion-rome-2017-app-dev-in-cloud-monkeys.html
Presentation on concepts for real time IoT analytics. Leveraging Azure technologies in the cloud and on the edge.
Topics covered: Azure Stream Analytics, IoT Edge, Azure Databricks, Event Grid , Python, Json
Real-time analytics in IoT by Sam Vanhoutte (@Building The Future 2019)Codit
The number of IoT devices that streams data to a connected cloud backend increases daily. This data creates new possibilities for real-time analytics and can fundamentally change how our world works. In this presentation, you’ll learn how to build an Azure IoT architecture that is ready for real-time data analytics. Sam will demonstrate how data can be ingested and how different Azure technologies can be applied to achieve real-time intelligence. You’ll also discover how Azure Stream Analytics can be used to run streaming queries in the Cloud and on the Edge. By the end of this session you’ll have an understanding on how Azure Time Series Insights works to set up a Real Time data exploration, and you’ll get a glimpse of Azure Databricks for more advanced data analytics scenarios. Finally, you’ll learn how to deploy custom code to detect and act upon events in the data.
Real time Analytics in IoT - Marcel Lattmann Codit Switzerland @.NET Day 2019Codit
The number of IoT devices which stream data to the cloud increases daily. In this practical session, we will build an end-to-end architecture for real-time analytics using the latest IoT technologies like IoT edge and data bricks.
Build a production AI in the cloud in 20 minutes!aiclub_slides
How to easily build production AI in the cloud. This presentation covers the common tools available from different cloud vendors and an easy way to link them together to build a full end to end AI in 20 minutes or less. We also cover REST microservice deployment.
Talk presented at droidcon Italy - April 8th 2016
Is Android truly ready for business-critical industrial solutions?
In this talk I’ll present project experiences, advantages and issues moving industrial enterprise solutions used by Fortune 500 companies from Windows mobile devices to Android covering topics like:
• Security
• Staging and managing devices
• Policy Controllers
• Single-use devices
• Managing updates and HW obsolescence
If you’re thinking that Android for Work is enough for a line-of-business industrial application, think again
IoT and the Autonomous Vehicle in the Clouds: Simultaneous Localization and M...Spark Summit
Processing real-time analytics of big data streams from sensor data will continue to be an important task as embedded technology increases and we continue to generate new types and ways of data analysis, particularly in regard to the Internet of Things (IoT). Robotics models many of these key challenges well and incorporates the possibility of high- throughput streams as well as complex online machine learning and analytics algorithms. These challenges make it an almost ideal candidate for in depth analysis of real-time streaming analytics.
We look at a simultaneous localization and mapping (SLAM) problem, an ongoing research area in robotics for autonomous vehicles, and well recognized as a non-trivial problem space in both industry and research. We will use a new integrated framework on Kafka and Spark Streaming to explore a constrained SLAM problem using online algorithms to navigate and map a space in real time.
We present benchmarks of our open-source robot’s integration with Kafka and Spark Streaming for performance against other SLAM algorithms currently in use, explore some of the challenges we faced in our implementation, and make recommendations for improvement of performance and optimization on our framework.
Finally, new to this talk, we demo real-time usage of our implementation with the Turtlebot II and explore relevant benchmarks and their implications on the future of autonomous vehicles in the IoT and cloud analytics space.
We are searching the unknown. How can you find hidden and unknown relationships in unrelated relational data silos? How can you search the relevant information in a 10^56 dimensional space? How do you create a consistent yet up to date information network for over 20 languages on a daily basis? And how on earth do you convince IT governance to let you use Solr for this kind of job? All this sounds impossible? This talk will give the answers and present a detailed case study and success story about how we used Apache Solr to build a search based business intelligence and automotive information research application for a major German car manufacturer. This talk has been presented at the Lucene/Solr Revolution 2016 in Boston. #LuceneSolrRev #ApacheSolr #qaware
Automotive Information Research driven by Apache SolrQAware GmbH
Lucene Revolution 2016, Boston: Talk by Mario-Leander Reimer (@LeanderReimer, Principal Software Architect at QAware).
Abstract: We are searching the unknown. How can you find hidden and unknown relationships in unrelated relational data silos? How can you search the relevant information in a 10^56 dimensional space? How do you create a consistent yet up to date information network for over 20 languages on a daily basis? And how on earth do you convince IT governance to let you use Solr for this kind of job? All this sounds impossible? This talk will give the answers and present a detailed case study and success story about how we used Apache Solr to build a search based business intelligence and automotive information research application for a major German car manufacturer.
3 Things to Learn:
• How to use Solr as a reverse data engineering tool to chart and explore relational data silos and their hidden relationships.
• Different approaches for de-normalizing relational data models efficiently without suffering combinatorial explosion like using multi-value fields, child documents or JavaScript validity term based post filtering.
• How to develop a rock solid, scalable, performant enterprise solution with complex business logic on top of Solr and Java EE.
Quantum computing takes a giant leap forward from today’s technology—one that will forever alter our economic, industrial, academic, and societal landscape. This has massive implications for your customers in any industry including healthcare, energy, environmental systems, smart materials, and more. Learn how Microsoft is taking a unique revolutionary approach to quantum and how your customers can get started developing quantum solutions with the Quantum Development Kit.
2016 02-04 howard look tidepool attd 2016 v2Tidepool
Tidepool CEO Howard Look
Presentation at the 9th International Conference on Advanced Technologies & Treatments for Diabetes (ATTD 2016) in Milan, Italy, 4 February, 2016
AWS IoT is a managed cloud platform that lets connected devices easily and securely interact with cloud applications and other devices. As an IoT developer, you will want to interact with AWS services like Kinesis, Lambda, and Amazon Machine Learning to get the most from your IoT application. In this session, we will do a deep dive on how to define rules in the Rules Engine, or retrieve the last known and desired state of device using Device Shadows, learn about the use cases and benefits of AWS Greengrass, and routing data from devices to AWS services to leverage the entire cloud for your Internet of Things application.
Similar to Using Amazon Machine Learning to Identify Trends in IoT Data - Technical 201 (20)
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.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
Generating a custom Ruby SDK for your web service or Rails API using Smithyg2nightmarescribd
Have you ever wanted a Ruby client API to communicate with your web service? Smithy is a protocol-agnostic language for defining services and SDKs. Smithy Ruby is an implementation of Smithy that generates a Ruby SDK using a Smithy model. In this talk, we will explore Smithy and Smithy Ruby to learn how to generate custom feature-rich SDKs that can communicate with any web service, such as a Rails JSON API.
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
2. What We’ll Cover Today
• Overview of AWS IoT and Amazon Machine Learning
• Anomaly Detection – What? Why? How?
• How to Build an IoT Solution using Machine Learning
based Anomaly Detection
3. AWS IoT
Securely connect one or one billion devices to AWS,
so they can interact with applications and other devices
8. Amazon Machine Learning
Based on What You
Know about an Order:
Is this Order
Fraudulent?
Based on What You
Know about the User:
Will they Use Your
Product?
9. Amazon Machine Learning
Based on What You Know
about a News Article:
What Other Articles are
Interesting?
Based on What You
Know about an Order:
Is this Order
Fraudulent?
Based on What You
Know about the User:
Will they Use Your
Product?
18. Behaviour Modes
• Entering Road
• Exiting Road
• Driving Between Intersections
• Stopped at Lights
• Waiting for Clear Path to Turn
• Waiting for Pedestrian
• Parking at Kerb
19. Unexpected Behaviours
• Car off Road
• Cars Stopped for Long Periods
• Erratic Driving
• More Traffic or More Messages than Expected
20. Supervised Machine Learning
The model is trained using historical data (or observations)
that are labeled with accurate answers for the problem
under analysis.
lat long elev vel heading activity
33.63078996 153.2408174 65.962 14.6 88.1 driving
33.61899274 153.4826805 64.732 0.6 163.8 parking
33.67753203 153.2248169 67.682 1.58 321.4 entering
33.10896801 153.0650639 61.006 27.52 145.9 driving
33.91719004 153.952396 53.305 0.0 60.0 at_lights
33.08905011 153.7517515 64.59 0.05 122.9 waiting
33.44729954 153.8196027 48.619 22.02 349.6 driving
exiting
Target
column
24. How Do We Build The Training Data?
lat long elev vel heading activity
33.63078996 153.2408174 65.962 14.6 88.1 ?
33.61899274 153.4826805 64.732 0.6 163.8 ?
33.67753203 153.2248169 67.682 1.58 321.4 ?
33.10896801 153.0650639 61.006 27.52 145.9 ?
33.91719004 153.952396 53.305 0.0 60.0 ?
33.08905011 153.7517515 64.59 0.05 122.9 ?
33.44729954 153.8196027 48.619 22.02 349.6 ?
33.85352192 153.4845429 48.265 5.49 251.1 ?
... … … … ... …
25. Trivial to get the data
RULES ENGINE
iotTrafficApp
SELECT * FROM ’myiotapp/cars'
"actions":
[{
”s3": {
”bucketName": ”iotTrafficApp",
“key” : “car-data/${timestamp()}”
"roleArn":"arn:aws:iam:…:role/aws_iot_s3”
}
}]
34. Building Secure Applications: A Reminder
def updateCar(id, data):
assert ID_re.matches(id)
assert isinstance(data.ma
assert isinstance(data.mo
35. Six Steps to Getting it Done
Cluster Analysis Build Predictive Model Run Predictions
Handle Critical Risks Assess Anomalies Iterate
driving: 0.007642,
parking: 0.908068,
exiting: 0.00581
33.6189 153.482 64.732 0.6 163.8
36. AWS Training & Certification
Intro Videos & Labs
Free videos and labs to
help you learn to work
with 30+ AWS services
– in minutes!
Training Classes
In-person and online
courses to build
technical skills –
taught by accredited
AWS instructors
Online Labs
Practice working with
AWS services in live
environment –
Learn how related
services work
together
AWS Certification
Validate technical
skills and expertise -
identify qualified IT
talent or show you
are AWS cloud ready
Learn more: aws.amazon.com/training
37. Your Training Next Steps:
ü Visit the AWS Training & Certification pod to discuss your
training plan & AWS Summit training offer
ü Register & attend AWS instructor led training
ü Get Certified
AWS Certified? Visit the AWS Summit Certification Lounge to pick up your swag
Learn more: aws.amazon.com/training