About The Event

The Global AI Bootcamp Singapore is a free two-days event organized by local communities that are passionate about artificial intelligence on Microsoft Azure.
Join us for the full day event on Azure to learn, share from the best minds from industry, experts and community leaders!

Where

Online

When

16th-17th January 2021

Event Schedule

We are having a great line-up speakers from around the world to share their passion, experiences in Azure with you!

Annie Mathew

AI and Ethics

Annie Mathew

Done well, AI can amplify human ingenuity. Done badly, however, it can create a plethora of new problems. At Microsoft, we’ve spent a lot of time thinking about the ethics of AI with a multidisciplinary group focused on the ethical impact of AI and other emerging data technologies. I’ll share the recommended corporate policies and principles to address the ethical, social, and societal issues raised by these technologies.

Marvin Heng

Create real value in your business process by automated data and form extraction

Marvin Heng

Business processes are crucial and documentation are often done with high human involvement. The possibilities of automating it can be valuable to us. Join us to explore, discuss and share more.

SANDEEP PAWAR

Model Interpretability using AzureML SDK

SANDEEP PAWAR

Machine learning model interpretability and explainability is as important model accuracy. It not only helps debug the model performance but can also help draw key insights from the data that business stakeholders can use to make strategic decisions. In this lightening talk, I will show how to use the model interpretability library in AzureML and its use cases.

Karan Balkar

Integrating Google Assistant for Continuous Integration (CI)

Karan Balkar

The talk aims to explain the steps to integrate Google Assistant using DialogFlow for Jenkins CI environment. It includes to steps to build an interaction model to know the status of the running jobs, run jobs (if not running) and automate the overall process.

Haritha Thilakarathne

Journey of a data point through Azure Machine Learning Studio

Haritha Thilakarathne

Azure machine learning studio is the new one-stop portal on Azure which enables you to design, depvelop and deploy complex machine learning workflows in a well managed manner. This sessions is a walkthrough on the capabilities of Azure machine learning studio with hands-on demonstration.

Prashant G Bhoyar

Introduction to AI and Cognitive Services for Microsoft 365 Developers and Information Workers

Prashant G Bhoyar

“Artificial Intelligence and Machine Learning are the new buzzwords in the industry. Microsoft's vision is to make AI accessible to every enterprise, data scientist, developer, information worker, consumer and device everywhere in the world. AI has a big role to play in the enterprise space. The field of AI is progressing at a rapid pace. Without understanding the concepts behind these advanced technologies, developers and administrators will struggle to evaluate the potential impact of new tools and solutions. In this session, we will break down the concepts behind existing technologies, outline various tools available today, and discuss the direction of AI and ML for Microsoft 365 Developers. We will cover how developers, Power Users, and Information workers can take advantages of the Microsoft's AI and Cognitive Services offerings to build real-life enterprise solutions. You will learn: 1) Overview of Microsoft AI Platform 2) What are the cognitive services? 3) What tools are available today? 4) How to use Cognitive Services to implement real-life business solutions in Microsoft 365?

Ambarish Ganguly

Random Walk of the Penguins - 1st prize competition solution

Ambarish Ganguly

The talk will be on the 1st prize-winning solution in the Random Walk of the Penguins ( hosted by Driven Data ) and sponsored by NASA. This competition solution involves using Supervised ML and Time Series Algorithms

Kyle Akepanidtaworn

E2E ML Model Operations and ML Lifecycle Management with GitHub Actions and Azure ML

Kyle Akepanidtaworn

Do you know that over 85% of data science projects fail according to Gartner analyst Nick Heudecker. A report from Dimensional Research indicated that only 4% of companies have succeeded in deploying ML models to production environment. MLOps provides critical capabilities to enable machine learning in production, including model reproducibility & versioning, model auditability & explainability, model packaging & validation, and model deployment & monitoring. I am excited to demonstrate to you how you or your organization can easily set up a data science or machine learning project with automated training and deployment using GitHub Actions and Azure Machine Learning.

ujjwal kumar

Quantum machine learning and optimization

ujjwal kumar

Walk through the emerging quantum machine learning and optimization area, its usage and current applications.

André Melancia

Build your own KITT with Azure Cognitive Services

André Melancia

Cognitive services can recognise objects, faces, describe images, understand speech and language, perform advanced searches and so much more. You can use these services with Azure Bots and IoT to build human interactive cars and houses, or simply interact with clients. If you are a developer and know nothing about Azure Cognitive Services, this is a good place to start. Disclaimer: Azure Cognitive Services can't drive a car. They're not 18 years old yet.

M A Nakib

AI Experiences with Power Virtual Agent

M A Nakib

Easily integrate your chatbots with the products and services you use every day. Look up records, personalize conversations, handoff conversations to live agents, and call APIs. Choose from hundreds of pre-built connectors, build custom workflows using Power Automate, or create complex scenarios with Microsoft Bot Framework.

Bruno Capuano

Let’s code a drone to follow faces syncing everything with Azure IoT

Bruno Capuano

You can control a drone using 20 lines of code. That’s the easy part. However, adding extra features like face or object detection and program the drone to follow and object or a face requires … another 20 lines of code! During this workshop we will review how to connect to a drone, how to send and receive commands from the drone, how to read the camera video feed and how to apply AI on top of the camera feed to recognize objects or faces. We will use a simple house drone ($100) and Python. And, when we review some enterprise scenarios, we will use Azure IoT to sync the drone information in IoT mode. Let’s build this!

Pio Balistoy

AI & ML in SQL Server 2019

Pio Balistoy

SQL Server 2019 boasts tons of new features enabling it to be the hub for all your data. In this session we will focus on the new features of SQL server 2019 for all your AI and ML needs. Why move your data around when you can do it all in SQL server 2019? Join the session to find out how.

Prashant G Bhoyar

Building Intelligent Enterprise-Grade Help Desk Bots using Conversational AI

Prashant G Bhoyar

Microsoft's CEO Satya Nadella has said: "Human Language is the new UI layer, bots are like new application". As more and more bots are getting popular in homes and enterprises, the demand for custom bots is increasing at rapid space. The Microsoft Bot framework is a comprehensive open source offering that we can use to build and deploy high-quality bots. Microsoft Cognitive Services let you build apps with powerful algorithms to see, hear, speak, understand and interpret our needs using natural methods of communication, with just a few lines of code. Easily add intelligent features – such as emotion and sentiment detection, vision and speech recognition, language understanding, knowledge, and search – into your app, across devices and platforms such as iOS, Android, and Windows, keep improving and are easy to set up. In this demo-driven session, we will cover how to build the enterprise-grade intelligent bots in using Microsoft Bot Framework and Cognitive Services and deploy in multiple platforms (channels) like Microsoft Teams, SharePoint, Public-Facing Web Sites, etc You will learn: What is Microsoft Bot Framework? What is Azure Bot Service? How to create bots using Microsoft Bot Framework? What are Cognitive Services? How to leverage Bot Framework and Cognitive Services to implement enterprise-grade bots? How to deploy Bots to Microsoft Teams, SharePoint and Public facing Websites?

Renganathan Palanisamy

Preparing for Data and AI Driven Future

Renganathan Palanisamy

This session is aimed to address the concerns of undergraduates and future workforce on how they can prepare for Data and AI Driven Future. Sharing of needed skills and available resources to be part of the Data and AI community

Priyanka Shah

Face Recognition and Visual Search with Azure Cognitive Services

Priyanka Shah

Azure Cognitive services package AI as APIs ready to use with in our applications. Two such compelling offerings are Azure Face services and Bing visual search. Face API is a part of Cognitive vision service that enables face recognition, detection, emotion identification etc. Whereas bing visual search helps interpret images to create compelling visual experiences. Bing search can be used to recognise celebrities, monuments, artwork, identify barcodes or extract text from image, enrich search experience with visually similar images and more- all through the single API. Let us walkthrough these exciting services and their usage in applications to provide rich insights

SANDEEP PAWAR

Time Series Forecasting in Power BI

SANDEEP PAWAR

Time Series Forecasting is essential for any size business to prepare and plan for the future. While Power BI has an in-built forecasting feature that is easy to use, it is severely limited, poorly documented and often misused. In this session, I will explain how Power BI forecasting works, its strengths/limitations, how to overcome those limitations and create an advanced forecasting model.

Håkan Silfvernagel

Machine learning in the browser using TensorFlow.js

Håkan Silfvernagel

In order to start out with machine learning you typically would need to learn Python, Tensorflow, Jupyter Notebook etc. But what if you could run your machine learning straight in the browser. This can be done through Tensorflow.js. In this session you will get an introduction so that you can use it in your own projects. This session will give you an introduction to what Machine learning is and what types of problem you can solve. TensorFlow as a library will be introduced and then TensorFlow.js will be presented with a focus on how you can use a machine learning model in your JavaScript application. Next, we will build an image classification web app that uses a predefined TensorFlow model. Finally, some examples on how TensorFlow.js is used in commercial applications will be given.

Luis Beltran

Transfer Learning for Deep Learning using TensorFlow & ML.NET

Luis Beltran

Transfer learning is a machine learning technique in which a model that was developed for an initial task serves now as the starting point for a model on a second duty. It is quite useful in Deep Learning since compute and time resources are limited, so you a pre-trained model can be used as an input for a computer vision or natural language processing task. Let's demonstrate how Transfer Learning works in ML.NET by exploring the following scenario: - Firstly, a pre-trained TensorFlow Inception model deep learning model will be incorporated in an ML.NET workflow. - Then, transfer learning is applied to this model using the ML.NET Image Classification API in order to create a new, custom deep learning model that identifies specific image categories. All the knowledge gained when solving the initial classification problem is useful for shortcutting another training process and solve a second classification. - If time allows it, we can deploy this model into a web API for consumption from another application (such as a mobile app)

Eldert Grootenboer

Building Smarter Solutions Using Azure And Cognitive Services

Eldert Grootenboer

There's a lot of discussion going on around Artificial Intelligence, and for good reason. AI and Cognitive Services are getting more powerful all the time, and it can be confronting to see all these developments. But how can we leverage this power in our own solutions, using it for making the life of our users and customers easier? In this session, you will see learn we can get data from the real world, and use this to drive our business, and all this in a serverless manner. Thanks to Microsoft Cognitive Services it's easy to integrate and work with speech, text, images and videos into our processes. Come and learn how to use this to your own advantage, driving your business forward.

Saravanan  Ganesan

Perform image classification at the Azure IoT edge with Custom Vision Service

Saravanan Ganesan

Azure IoT Edge can make your IoT solution more efficient by moving workloads out of the cloud and to the edge. This capability lends itself well to services that process a lot of data, like computer vision models. The Custom Vision Service lets you build custom image classifiers and deploy them to devices as containers. Together, these two services enable you to find insights from images or video streams without having to transfer all of the data off site first. Custom Vision provides a classifier that compares an image against a trained model to generate insights.

André Melancia

Azure Machine Learning and Cognitive Services [WORKSHOP v4]

André Melancia

This training will introduce you to Machine Learning and AI services and tools in Azure. The session will cover Azure ML, Spark using Azure Databricks, Azure Synapse Analytics, HDInsight, SQL Server Machine Learning services, Cognitive Services tools and will provide for hands-on experience as well. Machine learning is a data science technique that allows computers to use existing data to forecast future behaviour, outcomes, and trends. By using machine learning, computers learn without being explicitly programmed. Forecasts or predictions from machine learning can make apps and devices smarter. For example, when you shop online, machine learning helps recommend other products you might want based on what you've bought. Or when your credit card is swiped, machine learning compares the transaction to a database of transactions and helps detect fraud. And when your robot vacuum cleaner vacuums a room, machine learning helps it decide whether the job is done. Azure Machine Learning, Spark using Azure Databricks and Azure Synapse Analytics, are cloud services that you use to train, deploy, automate, and manage machine learning models, all at the broad scale that the cloud provides. Azure Cognitive Services are APIs / SDKs / services available to help developers build intelligent applications without the need for AI or data science skills or knowledge. Azure Cognitive Services enable developers to easily add cognitive features such as emotion and video detection; facial, speech, and vision recognition; and speech and language understanding – into their applications. The goal of Azure Cognitive Services is to help developers create applications that can see, hear, speak, understand, and even begin to reason. Attendees that want to try the examples during the workshop need to bring: * Laptop * Have an Azure subscription (e.g. set up a free trial at https://azure.com/free , use an Azure Pass free trial, or use a paid subscription); * Your preferred development IDE (e.g. Visual Studio 2019 Community Edition or Visual Studio Code) already installed, to access online webservices; * Excel (2013 or more recent); Note: C# examples will be covered, but the webservices can work with any programming language in your applications. Contents: 1. Introduction to Machine Learning (generic - from scratch, no pre-requisite needed) 2. Introduction to Azure Machine Learning technologies: Azure Machine Learning, Spark with Azure Databricks, Azure Synapse Analytics, HDInsight, SQL Server ML Services with R or Python, etc. 3. Introduction to Azure Cognitive Services and Bots

Event Speakers

Here are some of our speakers

Speaker 1

Ambarish Ganguly

NASA Citizen Scientist , TCS Data and Analytics Practice Lead , ETRM Practice Lead

Speaker 1

André Melancia

Developer / DBA / Microsoft Certified Trainer (MCT)

Speaker 1

Annie Mathew

APAC Developer Relations at Microsoft

Speaker 1

Bruno Capuano

AI Dude - Microsoft AI MVP

Speaker 1

Eldert Grootenboer

Cloud Solution Architect - Azure MVP

Speaker 1

Håkan Silfvernagel

Manager AI and Big Data

Speaker 1

Haritha Thilakarathne

Microsoft MVP - Artificial Intelligence

Speaker 1

Karan Balkar

Mobile Application Developer at LTI

Speaker 1

Kyle Akepanidtaworn

Microsoft, Global Cloud Solution Architect

Speaker 1

Luis Beltran

Microsoft MVP, Xamarin Certified Mobile Developer

Speaker 1

M A Nakib

Azure MCT, Asst. Manager on Cloud Solutions at Corporate Projukti Limited

Speaker 1

Marvin Heng

Technology Evangelist

Speaker 1

Pio Balistoy

Lead Data Platform Consultant - Pythian Services | Microsoft MVP - Data Platform

Speaker 1

Prashant G Bhoyar

Microsoft AI MVP, Senior Solution Architect-Intelligent Process Automation at Withum

Speaker 1

Priyanka Shah

Solution Architect, Franklin Templeton

Speaker 1

Renganathan Palanisamy

Data Specialist and MCT Regional Lead

Speaker 1

SANDEEP PAWAR

Simulation & Data Analytics Engineer

Speaker 1

Saravanan Ganesan

L&T infotech _ Module Lead _ IIoT

Speaker 1

ujjwal kumar

Lead Architect, Microsoft Corp

Sponsors