AWS Innovate Online Conference 2019 - Machine Learning & AI Edition

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Welcome to AWS Innovate Online Conference –
Machine Learning and AI Edition

Welcome to AWS Innovate Online Conference – Machine Learning and AI Edition, designed for data scientists, executives, IT professionals, data engineers and developers, who are looking to bring new ideas to reality. Hear the very latest from Swami Sivasubramanian, VP of AI and Machine Learning, AWS and Oliver Klein, Head of Emerging Technology, AWS, APAC during the AI and ML keynote.

Dive deep into any of the 20+ breakout sessions across six tracks delivered by AWS experts. This free online conference is designed to provide you with a platform to learn how to build, train and deploy sophisticated models with any framework and unlock an intelligent tomorrow, today.

From the world's largest enterprises to emerging start-ups, more machine learning is built on AWS than anywhere else.

AWS customers use machine learning to improve the quality of healthcare, fight human trafficking, provide better customer service, and protect you from fraud. With the broadest and deepest set of machine learning and AI services, they are creating new insights, enabling new efficiencies, and making more accurate predictions. That's why more than 10,000 customers have chosen to use AWS for machine learning.

+10,000

customers

[Will be hidden on mobile]

81%

of all deep learning is running
on AWS

85%

of TensorFlow projects in the cloud happen on AWS

Event Agenda

Click here to download agenda

Event Agenda

Session Description

  • Application of AI/ML
  • Build & Deploy ML Models
  • End to End Machine Learning
  • Fully Managed AI/ML Services
  • Coding
  • Demo Arena
  • Closing
  • Application of AI/ML
  • Build Business Outcomes with AI/Machine Learning (Level 200)

    AI and ML is the new normal. This session is intended as an introduction to how AWS customers are building intelligent business systems powered by AI and ML. Learn how these services, in conjunction with the large number of complementary AWS technologies, provide a great platform for our customer to build their own AI and ML powered solutions and drive business value. Towards the latter part of this session, hear directly from our customers about their AI and ML Journey on AWS.

    Speaker: Barnam Bora, Head of AI & Machine Learning, AWS, APAC

    Supervised and Unsupervised Machine Learning - The Type of Machine Learning to Use (Level 200)

    We potentially know about a few use cases of Machine Learning and the need for models to be trained successfully to cater to the use cases. Have you ever wondered as to whether the algorithms you use to train models differ based on level of difficulty, the amount of labelled data required and complexity? Do algorithms belong to the different categories? This session lists out the broad categories in which ML algorithms fall under, and get into details of what and when a type of algorithm or a learning model is more suited than others. We also look at the built-in algorithms available with Amazon SageMaker, their categorization, and the examples used. Learn from actual customer references to better understand the applicability of the different types of use cases.

    Speaker: Santanu Dutt, Senior Solution Architect Manager, AWS, ASEAN

    Empowering Customer Service with Amazon Connect and Machine Learning (Level 300)

    Customer experience remains one of the most important strategic measurements for organisational performance but, keeping pace with customer behaviour can be challenging. 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. Using the Amazon Connect integration with the machine learning services on AWS, you can use self-service configuration tools to accomplish in days what would often have taken months like building chatbots into customer call workflows. In this presentation, we will show you how Amazon Connect can be integrated with Amazon Transcribe, Amazon Comprehend, and Amazon Lex to enable organisations to deliver transformational omni-channel experiences to their customers.

    Speaker: Sumit Patel, Enterprise Solution Architect, AWS, ANZ

    An Overview of Amazon SageMaker Security (Level 100)

    Amazon SageMaker is a fully managed machine learning service that data scientists and developers use to build predictive and analytical models with their data. Organizations often need to use sensitive data to train models and generate predictions. In this session, we present the approaches taken to construct Amazon SageMaker with a security standard that would let the most security-conscious organizations do machine learning with confidence, as well as, the specific security-related features offered by the service.

    Speaker: Tom Faulhaber, Principal Software Engineer, AI Platforms, AWS

  • Build & Deploy ML Models
  • Getting Started with Amazon SageMaker - Build, Train, and Deploy Machine Learning Models (Level 200)

    Amazon SageMaker provides every developer and data scientist with the ability to build, train, and deploy machine learning models quickly at any scale. Amazon SageMaker takes away the heavy lifting of machine learning, thus removing the typical barriers associated with machine learning. In this session, dive deep into the technical details of each of the modules of Amazon SageMaker which showcases the capabilities of the platform. Learn from the practical deployments of Amazon SageMaker through real-world customer examples.

    Speaker: Tapan Hoskeri, Solution Architect, AISPL

    Opensource ML Frameworks on Amazon SageMaker featuring TensorFlow, PyTorch, MXnet, Keras, Gluon (Level 300)

    Amazon SageMaker provides every developer and data scientist with the ability to build, train, and deploy machine learning models quickly. Amazon SageMaker automatically configures and optimizes TensorFlow, Apache MXNet, Chainer, PyTorch, Scikit-learn, and SparkML so you do not have to do any setup to start using these frameworks. In this session, we look at how to use these frameworks with Amazon SageMaker and enable seamless movement of workloads between Amazon SageMaker and your infrastructure.

    Speaker: Aparna Elangovan, Solutions Architect, AWS, ANZ

    Reinforcement Learning with AWS DeepRacer and Amazon SageMaker RL (Level 300)

    Reinforcement Learning (RL) is both an exciting area of research and a driver of new commercial applications in the broader field of Machine Learning. In 2018, AWS released several new services that make it much simpler for data science and development teams alike to start exploring and applying RL. Join this session to understand how, with some basic python knowledge, you can get started with writing a reward function that teaches a small RC car to navigate its way around a race track autonomously. For those who want to apply RL to their own use cases, we dive into the features of Amazon SageMaker RL.

    Speaker: James Ousby, Senior Solutions Architect, AWS, ANZ

    ML Model Deployment Techniques using Amazon SageMaker Managed Deployment, Amazon Elastic Inference, Amazon Neo and AWS Inferentia

    Machine Learning can be very resource intensive and you will not be able to deploy a Machine Learning model until it is trained. At AWS, we are constantly working to make training models efficient, faster and cheaper. However, model inference is where the value of Machine Learning is delivered. This is where speech is recognized, text is translated, object is recognized in a video, manufacturing defects are found, and cars get driven. This session analyzes the common pain points we face in running Machine Learning and Deep Learning inference workloads. It also explains how AWS is addressing these pain points as you add intelligence to your applications and scale these workloads.

    Speaker: Atanu Roy, AI Specialist Solution Architect, AISPL

  • End to End Machine Learning
  • Build Your Data Lake Easily with AWS Lake Formation (Level 200)

    Setting up and managing data lakes today involves a lot of complicated and time-consuming tasks. AWS Lake Formation is a new service that will makes it easy to set up a secure data lake in days. You will be able to ingest, catalog, clean, and secure your data. Explore how AWS Lake Formation makes it easier to combine analytic tools, like Amazon EMR, Amazon Redshift, Amazon Athena, Amazon SageMaker, and Amazon QuickSight with the data in your data lake.

    Speaker: Unni Pillai, Specialist Solution Architect, Big Data and Analytics, AWS, ASEAN

    Machine Learning at the Edge (Level 200)

    Advances in data analytics tools have enabled data driven decision making. However, it is not always possible to send data to the cloud to be processed. In this session, learn how to train machine learning models using Amazon SageMaker and deploy them to an edge device using AWS Greengrass. Find out how to enable and process data quickly at the edge, even when there is no connectivity.

    Speaker: Kapil Pendse, Partner Solution Architect, AWS, ASEAN

    Accurately Automating Dataset Labelling using Amazon SageMaker GroundTruth (Level 200)

    Successful machine learning models are built on high-quality training datasets. Labeling raw data to get accurate training dataset involves a lot of time and effort, because sophisticated models can require thousands of labeled examples to learn from, before they produce good results. Typically, the task of labeling is distributed across large number of humans, adding significant overheads and costs. In this session, learn how Amazon SageMaker Ground Truth can solve data labeling problems, build highly-accurate training datasets, and achieve automated labeling.

    Speaker: Will Badr, Senior Technical Account Manager, AWS Enterprise Support, ANZ

    Building Serverless Machine Learning Workflows (Level 300)

    Modern machine learning workflows leverage AWS services, such as Amazon Transcribe and Amazon Comprehend, to extract, validate, mutate, and enrich your data. Some might drive transactional systems that use machine learning to generate metadata for media assets, while others might derive insights by visualizing customer interaction sentiment from call logs. They all share a common challenge, orchestrating a combination of distinct sequential and parallel steps that are fulfilled by independent microservices. Join us as we examine how workflows can be used to manage that orchestration in a way that is scalable, reliable, and easy to maintain and run, and also how to perform CI/CD for machine learning model training and deployment with AWS Step Functions.

    Speaker: Donnie Prakoso, Technology Evangelist, AWS, ASEAN

  • Fully Managed AI/ML Services
  • Amazon.com's AI techniques - Personalize Customer Experience and Forecast Accurately using Amazon Personalize and Amazon Forecast (Level 200)

    Join us to understand how any developer and IT professional can make use of Amazon.com’s forecasting and recommendation machine learning algorithms using Amazon Forecast and Amazon Personalize. Learn how to train these services with your own data and make accurate predictions in a very short period of time. Understand how to use Amazon Personalize to allow real-time personalization and recommendation, with the same technology used at Amazon.com and without the need of any prior ML expertise.

    Speaker: Olivier Klein, Head of Emerging Technologies, AWS, APAC

    Computer Vision - Image and Video Analysis featuring Amazon Rekognition, Amazon Textract (Level 200)

    In this session, dive deep into the Amazon Rekognition and Amazon Textract services. These fully managed computer vision AI services, provide the ability to identify objects, people, text, scenes, and activities, as well as, detect any inappropriate content. Furthermore, they allow extraction of content intelligently from existing documents and forms. We will also explain the usage of these services and provide live demonstrations.

    Speaker: Shaun Ray, Evangelist Manager, AWS, APAC

    Add Intelligence to Your Applications with AWS Natural Language Processing services (Level 200)

    IDC researchers have predicted that 60 percent of IT application decisions will be based on technology provider's ecosystem including innovators in machine learning, natural language processing and cloud by 2022. In this session, learn how you can reimagine your customer experience for voice with Alexa skills and gain valuable insights on how Amazon Lex conversational virtual agents enable your contact center to scale. Discover insights and relationships in text with Amazon Comprehend, and how Amazon Textract provides insights from mass unstructured texts and documents collected and stored over the years. Whatever the use case, Natural Language Processing (NLP) and Natural Language Understanding (NLU) are fundamental components to add intelligence to your applications. This session covers NLP/NLU technologies provided by AWS pre-trained AI services to allow for ready-made intelligence for your applications and workflows with no ML experience required.

    Speaker: Dean Samuels, Senior Solution Architect Manager, AWS

  • Coding
  • Introduction to Machine Learning - Training Your Own Image Classifier with Amazon SageMaker (Level 300)

    Getting started with deep learning can feel really intimidating. In this session, we dive right in to explaining the basic concepts of deep learning with barely any jargon and only a bit of high-school math. Find out how easy it is to take an existing pre-trained general-purpose image classification model from the cloud and re-train it to identify specific classes of objects. Learn how to do all of this with python, using a Jupyter notebook hosted from Amazon SageMaker. Finally, we finished up with a review of where to continue learning more.

    Speaker: Gabe Hollombe, Technical Evangelist, AWS, APAC

    Using Amazon SageMaker for Fraud Prediction on Credit Card Transactions (Level 400)

    In this coding session, get insights on end-to-end machine learning in practice and dive deep on creating and detecting fraudulent transactions using Amazon SageMaker and AWS Lambda. Find out how to export the model outside of Amazon SageMaker.

    Speaker: Will Badr, Senior Technical Account Manager, AWS Enterprise Support, ANZ

  • Demo Arena
  • Smart Dermatology Demo

    Medical Imaging is a field which is seeing great benefits from machine learning techniques. It has potential to revolutionize access to healthcare, traditionally underserved populations, overcoming challenges like cost, remoteness of locations and poor doctor to patient ratios in overburdened healthcare systems.

    This demo showcases how Amazon SageMaker can help build intelligent software solutions which, aids in the diagnosis of skin conditions when presented with a picture of an affected area of the body.

    Learn how this workflow can be integrated with the larger healthcare ecosystem – including insurance providers, paramedical and medical professionals to benefit customers. Let us demonstrate how this software can be deployed on ‘edge’ computing devices like AWS DeepLens or a Raspberry Pi to perform this diagnostic activity without needing a connection to the Internet. This can be a boon to areas with limited mobile or internet access, or inhospitable terrain for example, allowing healthcare professionals to serve populations in these areas.

    Speaker: Tapan Hoskeri, Solution Architect, AISPL

    Intelligent Car Damage Assessment Demo

    Whenever your policyholder is involved in an accident, it is critical to quickly assess whether the car is repairable or not, and dispatch it to the right workflow the very first time. The current processes rely on dozens of subjective questions that are not accurate and instead of asking your customer to answer questions at a moment of stress, simply ask them to take a few images, or assign this to the tow truck driver. This demo shows you how to claim insurance damages, hassle free and intelligently.

    Speaker: Anand Iyer, Enterprise Solution Architect, AISPL

    Smart Parking Demo

    In modern cities, it is difficult and expensive to create more parking spaces for vehicles as there is an increase in numbers of vehicles running on the road in turn, reducing the number of the free parking spaces. Most public parking spaces have security cameras. What if we could use the advances made in neural networks to help people find vacant spaces? In this demo, we use a mobile application with Amazon SageMaker, Amazon Rekognition, AWS AppSync and AWS Amplify to showcase how users can reserve and navigate to parking spaces, detect unauthorized or expired parking. This enhances the security and also provides property management companies with the ability to analyze the utilization of the parking area.

    Speaker: Chandrashekar Munibudha, Solution Architect, AISPL

    Intelligent Customer Identification Demo

    Know Your Customer (KYC) is the process of verifying the identity of your customers based on the receipt of government issued documents. Regulations are becoming increasingly strict for financial services providers and market participants to include KYC as a part of their process. Failure to do so invites penalties and loss of reputation. This process is completely manual and time consuming. Critical PII data needs to change hands at various touchpoints leading to potential security data leaks.

    In this intelligent customer identification demo, we use Raspberry Pi, together with a few generally available peripherals to simplify the whole KYC process. Find out how you can verify documents in less than 30 seconds using services that are ISO certified, with minimal human intervention. Join us in this session to see how simple it is to build such an application from scratch!

    Speaker: Gaurav Jagavkar, Solution Architect, AISPL

  • Closing
  • Outlook on Automation and Robotics

    To close out we have an overall outlook on automation driven by AI/ML and look ahead at future possibilities and trends. We also have a deeper discussion about the space of robotics and AWS RoboMaker. This will include a live demonstration on how to quickly and effectively build smart and intelligent mobile robots that are enhanced using reinforcement learning, navigational and cognitive capabilities. Don’t miss out TurtleBot3 roaming the AWS Innovate studio in real-time.

    Speakers:
    Olivier Klein, Head of Emerging Technologies, AWS, APAC
    Dean Samuels, Senior Solution Architect Manager, AWS

Level 100
Introductory
Sessions are focused on providing an overview of AWS services and features, with the assumption that attendees are new to the topic.
Level 200
Intermediate
Sessions are focused on providing best practices, details of service features and demos with the assumption that attendees have introductory knowledge of the topics.
Level 300
Advanced
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.
Level 400
Expert
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.
Why Attend
Why Attend
We recognize customers are in different stages of AI and ML solution adoption journey, from exploration to super-users and everything in between. This conference will enable you to maximize innovation with access to scalable and flexible infrastructure.
Who Should Attend
Who Should Attend
Whether you are new to AWS or an experienced user, you can learn something new at AWS Innovate. AWS Innovate is designed to help you develop the right skills to create new insights, enable new efficiencies, and making more accurate predictions.

Featured Speakers

Swami Sivasubramanian, VP Amazon Machine Learning, AWS
Swami Sivasubramanian, VP, AI and Machine Learning , AWS

Swami is a vice president and general manager of Amazon AI and Machine Learning Services at AWS.

Previously, he was the general manager of NoSQL and Big Data Services at AWS, where he managed the design, product management, and operations for various big data services and major AWS database services, including DynamoDB, Amazon ElastiCache, Amazon QuickSight, and Simple DB. He holds more than 200 patents, has written more than 40 referenced scientific papers and journals, and has participated in numerous academics and conferences.

He has also built more than 20 AWS cloud services, including CloudFront, Amazon RDS, Amazon S3 and original Amazon Dynamo, and is one of the co-authors of Amazon Dynamo paper with Dr. Werner Vogles. 

Olivier Klein, Head of Emerging Technologies, AWS
Olivier Klein, Head of Emerging Technologies, AWS

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.

Dean Samuels, Solution Architect Manager, AWS
Dean Samuels, Solution Architect Manager, AWS

Dean comes from an IT infrastructure background and has extensive experience in infrastructure virtualisation and automation. Dean has been with Amazon Web Services for the last five years and has had the opportunity to work with businesses of all sizes and industries, primarily across Australia and New Zealand, but also across the wider APAC region.

Dean is committed to helping customers design, implement and optimise their application environments for the public cloud to allow them to become more innovative, agile and secure. Whilst Dean does have a strong IT infrastructure background covering compute, storage, network & security he is very focused in bringing IT Operations and Software Development practices together in a more collaborative and integrated manner.

FAQ

1. Where is AWS Innovate hosted?
2. Who should attend AWS Innovate?
3. What is the price of attending AWS Innovate?
4. Can I get a confirmation of my AWS Innovate registration?
5. How can I contact the online conference organizers?
6. Is there any Korean translation in AWS Innovate?

Q: Where is AWS Innovate hosted?
A: AWS Innovate is an online conference. Upon registration, you will receive a confirmation to access the platform using the log-in link provided.

Q: Who should attend AWS Innovate?
A: Whether you are new or an experienced user, AWS Innovate provides you with a platform to learn how you can use AWS to maximize innovation with access to scalable and flexible infrastructure.

Q: What is the price of attending AWS Innovate?
A: AWS Innovate is a free-to attend online conference.

Q: Can I get a confirmation of my AWS Innovate registration?
A: Upon completing the online registration process, you will receive a confirmation email.

Q: How can I contact the online conference organizers?
A: 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?
A: We have Korean translations for the Keynote. There are other sessions available in Korean language and these are chosen from the English sessions.