AWS Innovate Online Conference Special Edition - Machine Learning

Welcome to AWS Innovate Online Conference Special Edition – Machine Learning , designed for data scientists, developers, IT professionals and executives who are looking to bring new ideas to reality with Machine Learning on AWS. Whether you are new or an experienced user,AWS Innovate is designed to provide you with a platform to learn how to build sophisticated models with any framework and unlock an intelligent tomorrow, today

More machine learning is
built on AWS than anywhere else

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Date & Timezone

22 February 2018 (Thursday)

  • Timing 1

    Timing 2

  • Australia
    10:00am - 1:00pm (AEDT) 4:30pm - 7:30pm (AEDT)
  • New Zealand
    12:00pm - 3:00pm (NZDT) 6:30pm - 9:30pm (NZDT)
  • India
    4.30am - 7.30am (IST) 11:00am - 2:00pm (IST)
  • Singapore
    7:00am - 10:00am (SGT) 1:30pm - 4:30pm (SGT)
  • Korea
    8:00am - 11:00am (KST) 2:30pm - 5:30pm (KST)

Event Agenda

Duration
Session Titles
40 mins
Duration: 40 mins
Opening Keynote
Unlocking New Todays – Build for Tomorrow AWS is at the forefront of innovation in Artificial Intelligence (AI) and Machine Learning (ML) and, empowers businesses of all sizes to build their own innovation factories to deliver seamless experiences and, drive business automation at any scale. In this session, we will discuss the opportunities we see unlocked across industries. talk about the technologies now available for customers, from AI-assisted applications, to guided Machine Learning, to on-demand Deep Learning as well as share the vision of why we build and deliver what we do and what this means for our customers.
Duration: 30 mins

How Machine Learning is delivering Business Outcome

30 mins

Choosing the best AI technologies for your use case -- Application enablers vs Machine Learning vs advanced analytics vs deep learning (Level 100)

Wanting some guidance on when and how to apply different AI technologies? This session will walk through the technologies that you may be hearing about and when to use them. Want to know when a fully managed API is good enough, or is Machine Learning a better fit? What kinds of skills will you need to take advantage of technologies with deeper and richer capabilities.

30 mins

Seamless customer experiences -- remove boundaries between your customer and you (Level 200)

Provide customers with a natural experience that starts and stops without hard boundaries. In this session, we look at how to use a mixture of interfaces for use voice enablement, detection of movement, understanding of visual context, and response to intention. Increasingly, organizations are bringing services and products to customers in a way that doesn't disrupt the flow of their experiences.

30 mins

Automating the organization -- improve decision making and reduce inefficiencies (Level 200)

Transform business processes and physical operations through autonomous systems. In this session, we look at how to improve the interpretation of events and scenarios, to enable the confidence levels of decision making even to the point of automation. In contexts where physical operations are involved, we look and how to improve efficiency, accuracy, and safely when operating at scale.

Duration: 30 mins

Machine Learning - Key Services

Deep learning based Image and Video Analysis with Amazon Rekognition and Amazon Kinesis Video Streams (Level 300)

Image and video have been part of how we communicate nowadays and it has been a challenge for us to add visual analysis to our applications. Deep learning empowers us to analyze and understand them, presenting a new opportunity for business innovation. From sentiment analysis to person tracking, this session will explore how to easily add powerful image and video analysis with Amazon Rekognition. On top of that, we will also learn how to do real-time video analysis by integrating Amazon Kinesis Video Streams.

Natural Language Processing and Automated Speech Recognition for Data Analytics (Level 300)

Gain insights in your customers and data by utilising machine learning techniques to analyse customer contact centers call recordings, translate them into different languages, and use them for further analysis of what drives positive outcomes. Using Amazon Transcribe for speech to text, Amazon Translate for language translation and Amazon Comprehend for insights in unstructured text.

Empower your organization with Alexa for Business (Level 200)

Alexa for Business makes it possible for businesses to create Alexa skills designed specifically for employees or customers. With Alexa for Business, devices can be managed and provisioned to be used by employees in conference rooms, at employees’ desks, or around the workplace. In this session, we’ll provide an overview of Alexa for Business, and show you how Alexa for Business creates business value for both customers and employees.

Duration: 30 mins

Machine Learning Framework & Tools

Build, train, deploy ML models at scale with Amazon SageMaker (Level 400)

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 we will share 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.

Overview of the 10 most common ML algorithms (Level 400)

In this session, we will review general classes of Machine Learning problems and some of the high-speed algorithms available to solve them on Amazon SageMaker. The session will focuss on discussing what algorithms are suited for what kind of business problems. We will also discuss in brief the fundamental algorithm behind all deep learning: the backpropagation algorithm.

Run ML models at the edge with AWS Greengrass ML (Level 300)

In this session, we will discuss how you can integrate your Machine Learning models into an edge device using AWS Greengrass and make inference on your data. We will review the AWS IoT services that enable AWS Greengrass ML Inference to operate, showcase how you would go about setting up your edge device and finally demo local edge object recognition.

Duration: 30 mins

Machine Learning - Key Services, Framework & Tools

Building Intelligent Chatbots with Amazon Lex & Amazon Polly (Level 300)

AWS offers a family of AI services that provide cloud-native Machine Learning and Deep Learning technologies allowing developers to build an entirely new generation of apps that can hear, speak, understand, and converse with application users. In this session we take a look at Amazon Polly and Amazon Lex and how we can use these services to build intelligent chatbots across social media, websites and kiosks.

Building a call center in the Cloud with Amazon Lex and Amazon Connect (Level 300)

Customer experience remains one of the most important strategic measurements for organisational performance, but keeping pace with customer behaviour can be challenging. Virtual assistants (chatbots) provide one of the largest areas for growth and opportunities for business. Amazon Connect is a simple to use, cloud-based contact centre service that makes it easy for any business to deliver engaging customer service interactions. In this presentation, we’ll show you how to quickly set up an Amazon Connect contact centre, and use Amazon Lex and AWS Lambda to build intelligent conversational chatbots which you can use in your contact centre workflows to offer personalized and dynamic caller experiences for a better customer experience.

Using ML for Security at Scale with Amazon GuardDuty and Amazon Macie (Level 200)

Machine Learning has number of practical applications within the field of Information Security. Amazon uses Machine Learning to detect anomalies in AWS account and workload activity with Amazon GuardDuty. Amazon Macie also uses Machine Learning to automatically discover and classify sensitive data. Both of these services are recently released and provide new mechanisms and a new paradigm for customers to protect themselves in the AWS cloud. This talk will cover both services and provide examples of the output of the Machine Learning they use to help customers stay secure at scale on AWS.

Duration: 30 mins

Twitch,
Ask the Experts & Resources

Interactive Live Coding:
Build an AI-powered Twitter Bot with Python, AWS Lambda, and Amazon SageMaker Via AWS Twitch

In this interactive session, you’ll be able to watch and contribute as we live code a Twitter bot powered by AWS and Artificial Intelligence that can guess where in the world a picture was taken. Offer suggestions or ask questions during the coding session to influence the direction of the broadcast. We’ll explore the Twitter API, Amazon Sagemaker, Amazon DynamoDB, Boto3, Amazon API Gateway, and AWS Lambda. At the end of the broadcast, we’ll push the source code live and deploy the bot to production!

Duration: 30 mins

Korean Track
Machine Learning -
Key Services, Framework & Tools

Introduction to AWS based AI video Analysis Service (AWS 기반 인공 지능 비디오 분석 서비스 소개) (Level 200)

Amazon Rekognition을 이용한 이미지 분석 서비스에 이어 Amazon Rekognition Video는 실시간 및 저장된 동영상에서 객체 추출과 정보를 분석하여 서비스에 바로 적용이 가능합니다. 단순 객체 정보 외에 환경에 대한 정보와 개인 트래킹 정보를 제공하며 새로운 비디오 분석 서비스를 소개합니다. 또한 대량의 동영상 데이터를 저장하고 다른 서비스와 연계할 수 있는 Kinesis Video Streams 서비스를 소개합니다.

AWS의 새로운 통합 딥러닝 서비스, Amazon SageMaker (Level 300)

인공지능 전문가나 개발자들은 여전히 학습 모델을 만들기 위한 여러 단계의 과정을 구성하는데 시간을 씁니다. Amazon Sagemaker는 쉽고 빠르게 머신 러닝 모델을 만들어 학습시키고 배포하는 통합 서비스입니다. 시작과 함께 바로 Notebook 환경에서 모델을 구현하고 Docker container를 통해 학습하며, API Endpoint를 배포하는 새로운 서비스 Sagemaker를 소개합니다.

Amazon DeepLens와 컴퓨터 비전 딥러닝 어플리케이션 활용 (Level 300)

세계 최초로 딥러닝이 가능한 비디오 카메라 툴킷인 AWS DeepLens와 Amazon SageMaker 및 AWS Greengrass 서비스를 이용해서 딥러닝 기반의 컴퓨터 비전 어플리케이션을 쉽고 빠르게 개발하고 배포하는 방법을 소개합니다.

30 mins
Duration: 30 mins
Closing Remarks – Live Demo
20 mins
Duration: 20 mins
Ask the Experts

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 I would like to receive more information about other AWS events and services
Read more about Machine Learning from Forbes Insights:
  Innovation with Machine Learning
Learn how AI technologies such as machine learning and computer vision have launched new business models for Capital One in financial services and John Deere in agriculture. Gain insights on how machine learning has enabled these business leaders to make better decisions and give brands an endless opportunity to provide each customer a personalized experience.
 The Role of Machine Learning in Businesses
Find out how the President and CEO of Aon Benfield and CIO of Capital One use Machine Learning to achieve greater compute power, speed, agility, overcome organizational challenges and stay ahead of the competition.
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Speakers

  • Dr. Matt WoodGM, Artificial Intelligence, Amazon Web Services

    Dr. Matt Wood
    GM, Artificial Intelligence,
    Amazon Web Services

    Dr. Matt Wood is part of the technical leadership team at Amazon Web Services, pulling from over a decade of expertise in distributed systems, architecture, web-scale analytics, big data, machine learning and high performance computing to help customers bring their ideas to life through technology. After medical school, Dr. Wood completed his PhD in machine learning and bioinformatics, joined Cornell as a research fellow, and contributed to the next generation DNA sequencing platform at the Wellcome Trust Sanger Institute. Since joining Amazon Web Services in early 2010, he has played a role in introducing many significant new features and services to customers on the AWS Cloud, including Amazon SageMaker and AWS DeepLens.

  • Craig StiresHead of Analytics, Artificial Intelligence, and Big Data, Amazon Web Services, APAC

    Craig Stires
    Head of Analytics, Artificial Intelligence, and Big Data, Amazon Web Services, APAC

    Craig Stires is Head of Big Data and Analytics for Amazon Web Services, APAC. He works with some of the most innovative organizations across the region, as they architect analytics platforms and become data-driven. When he first moved to Asia, in 2001, he was designing and implementing analytics solutions for Customer Engagement, Risk Management, and Operational Analytics. After several years, he founded a startup in Thailand building predictive intelligence software. Following that, built the APAC Big Data research practice for industry analytics firm IDC. After years of advising clients to build scalable, optimized, and business-ready analytics platforms, the time was right to get hands-on again. Moving to the world's largest cloud services provider has opened the door to work together with customers to build some of their most exciting visions.

  • Glenn Gore Chief Solutions Architect, Amazon Web Services

    Glenn Gore
    Chief Solutions Architect, Amazon Web Services

    As the Chief Solutions Architect for Amazon Web Services, Glenn is responsible for creating architectural best practices and working with customers on how they use the cloud and innovation to transform their own businesses or disrupt new markets. Glenn has held previous roles in AWS, most recently as Head of Architecture for Asia Pacific and EMEA for Amazon Web Services where he managed regional teams working in the fastest growing region. Glenn has experience in working in mature and emerging markets, helping customers use the latest advancements to give them a competitive edge

  • Olivier Klein Emerging Technologies Solutions Architect, Amazon Web Services, APAC

    Olivier Klein
    Emerging Technologies Solutions Architect, Amazon Web Services, APAC

    Olivier is a hands-on technologist with more than 10 years of experience in the industry and has been working for AWS across APAC and Europe to help customers build resilient, scalable, secure and cost-effective applications and create innovative and data driven business models. He advises how emerging technologies in the Artificial Intelligence (AI), ML and IoT space can help create new products, make existing processes more efficient, provide overall business insights and leverage new engagement channels for end-consumers. He also actively helps customers build platforms that align IT infrastructure and service spending with revenue models, effectively reducing waste and disrupting how product development had been executed over the past decades.

  • Shaun Ray Head of Solutions Architect, Amazon Web Services, ASEAN

  • Adam Larter Developer Solutions Architect, Amazon Web Services, ANZ

  • Sumit Patel Solutions Architect, Amazon Web Services, ANZ

  • Phil Rodrigues Principal Solutions Architect, Amazon Web Services, ANZ

  • Donnie Prakoso Technology Evangelist, Amazon Web Services, ASEAN

  • Eric Heikkila WW Head of Business Development - AI,
    Machine Learning and Non-Relational Databases at Amazon Web Services

  • Tim Cruse IoT Specialist Solution Architect, Amazon Web Services, APAC

  • Koorosh Lohrasbi Solutions Architect, Amazon Web Services,ANZ

  • Girish Dilip Patil Sr. Solutions Architect, ML and Big Data, AISPL

  • Kiwaon Kim Solutions Architect, Amazon Web Services, Korea

  • Muhyun Kim Solutions Architect, Amazon Web Services, Korea

  • Junghee Kang Associate Solutions Architect, Amazon Web Services, Korea

  • Randall Hunt Senior Technical Evangelist, AWS

  • Dan Romuald Mbanga Business Development Manager, AI Platforms, AWS

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Session Details

  • Introductory

    Level 100

    Sessions are focused on providing an overview of AWS services and features, with the assumption that attendees are new to the topic.

  • Intermediate

    Level 200

    Session are focused on providing best practices, details of service features and demos with the assumption that there introductory knowledge of the topic.

  • Advanced

    Level 300

    Sessions dive deeper into the selected topic. Presenters assume that the audience has some familiarity with the topic, but may or may not have direct experience implementing a similar solution.

  • Expert

    Level 400

    Sessions are for attendees who are deeply familiar with the topic, have implemented a solution on their own already, and are comfortable with how the technology works across multiple services, architectures, and implementations.

Back to Agenda

FREQUENTLY ASKED QUESTIONS

  • Q: Where is AWS Innovate hosted? AWS Innovate is an online interactive conference. Upon registration to the conference you will receive a confirmation and on the live day you can access the platform.
  • Q: Who should attend AWS Innovate?This conference is designed for data scientists, developers, IT professionals and executives who are looking to bring new ideas to reality with Machine Learning on AWS. Whether you are new or an experienced user, AWS Innovate is designed to provide you with a platform to build sophisticated models with any framework and unlock an intelligent tomorrow, today.
  • Q: What is the price of attending AWS Innovate? AWS Innovate is a free-to attend online conference.
  • Q: Can I get a confirmation of my AWS Innovate registration?Upon completing the online registration process, you will receive a confirmation email
  • Q: How can I contact the online conference organizers?If you have questions that have not been answered in the FAQs above, please contact us at:aws-apac-marketing@amazon.com
  • Q: Is there any Korean translation in AWS Innovate?We have Korean translations for the Keynote. There are other sessions available in Korean language and these are chosen from the English sessions.