Sessions October 2021

Learning Deep Learning

Recently, Microsoft has released two Learning Paths on MS Learn covering ...

Anaam Sayeda

Watch session

Roundtable: MS Learn for Personal Development and In-Class

We will bring together some students as well as professors who have experie...

Amir Pourabdollah

Syed Farhan Ahmad

Dmitry Soshnikov

Anaam Sayeda

Rishit Dagli

Watch session

Recommendation Systems and their types In our daily lives

Recommendation systems are everywhere in this world from Netflix movie...

Kaushik Tummalapalli

Watch session

Computer vision made easy with Azure Custom Vision

Learn how to build a no-code image classification model with the Azure Cus...

Foteini Savvidou

Watch session

A Deep Dive Into Machine Learning

Come and see how you can integrate machine learning into your daily life a...

Narcisse Mbuyu

Watch session

Biometric Artificial Intelligence

A brief intro about the vast application of Artificial Intelligence and...

Sidharth Sudheer

Watch session

Implementation of Linear Regression using tfjs

- Introduction to Tensorflow.js - Architecture of TFJS - Project ...

Kartikey Rawat

Watch session

What it takes to be an NLP Engineer

Did you know? You don't need to be a Ph.D. or a Senior Professional to lear...

Usman Khan

Watch session

Introduction to Siamese Network

This session focuses on building a Siamese Network using TensorFlow functio...

Rohan Raj

Watch session

Project Plant AI

Just the other day I was reading some articles and I saw an online news ar...

Rishit Dagli

Rishabh Singh

Rucha Yagnik

Watch session

Introduction to Azure Health Bot

Azure Health Bot enables users to build a Health Bot by using built-in or...

Shreyan J D Fernandes

Yesasvini Sai Meghana Chikkam

Watch session

Artificial Intelligence in Public Transportation Systems

Artificial Intelligence has revolutionized every aspect of modern living....

Sanya Sinha

Watch session

#NoMoreMatildas

Artificial Intelligence (AI) is the pinnacle of digitization; it is a tech...

Carla Florida

Watch session

Can a Machine Learning System Outperform Humans in Emotion Recognition?

In 1961, when Carl Sagan learned that a NASA spacecraft to Venus would...

Valentina Zhang

Watch session

Roundtable: Women in Data Science

In this roundtable session, you will hear opinions of several students and...

Ornella Altunyan

Locksley Kolakowski

Anchal Bhalla

Watch session

Roundtable: MS Learn for Personal Development and In-Class

till

We will bring together some students as well as professors who have experience using Microsoft Learn to discuss the best strategy of learning AI/ML and using Microsoft Learn in the process.

Add to agenda

Amir Pourabdollah

Senior Lecturer at Nottingham Trent University

Syed Farhan Ahmad

Quantum Researcher, University of California Los Angeles

Dmitry Soshnikov

Cloud Developer Advocate, Microsoft

Anaam Sayeda

Microsoft Learn Student Ambassador

Rishit Dagli

TED-X, Ted-Ed speaker

Project Plant AI

till

Just the other day I was reading some articles and I saw an online news article on a recent suicide case of Indian farmers with the headline “Farmer couple commits suicide after killing minor”, this made my heart skip a beat. And I thought to address the problems of yield losses due to diseases with what I love, tech. Many Indian farmers or crop growers (since most of our research was based out of India) are not yet aware of the right kind of fertilizers, manure, or biocides, and also modern farming practices and crop diseases over the last year have led up to 67% yield losses among Indian farmers which is humongous portion!

Plant AI is a web application that helps to easily diagnose diseases in plants from plant images using Machine Learning available on the web. We provide an interface on the website where you can upload images of your plant leaves. The idea this project proposes to use smartphones which most farmers already have access to, to diagnose diseases in their crops through plant images early and in an accurate manner. The app would also provide the farmers with easy and actionable ways to solve the disease which would be quite helpful for most farmers since most plant diseases occur due to farmers being aware of the right techniques.

This project uses TensorFlow and Azure ML to train the ML models. Grappler (distributed with TensorFlow) and AzureML to optimize the model to run on-device on mobile phones. React and TensorFlow.js to build out the website and perform on-device inferences and Azure Static Web Apps and Azure Blob Storage in some aspects to host the web app. Finally, we also provide an API since though on-device inferences are the best option in most such cases, having the ML offloaded to the server-side could be quite useful in some scenarios and serve our API with Azure Kubernetes Services.

Add to agenda

Rishit Dagli

TED-X, Ted-Ed speaker

Rishabh Singh

Frontend & UI/UX Designer

Rucha Yagnik

Full-stack Developer

Introduction to Azure Health Bot

till

Azure Health Bot enables users to build a Health Bot by using built-in or custom scenarios. In this 4 part series we will explore different learning paths that will guide you through the creation of both a basic and enhanced Azure Health Bot. You'll learn about language understanding and how to use both built-in and template scenarios.
There will be demos to show the methods involved in creating a basic bot and further add capabilities like database connection, Interrupting scenario, Microsoft Teams App creation and so on to the same bot.

Add to agenda

Shreyan J D Fernandes

Microsoft Learn Student Ambassador

Yesasvini Sai Meghana Chikkam

Beta Microsoft Student Ambassador

Artificial Intelligence in Public Transportation Systems

till

Artificial Intelligence has revolutionized every aspect of modern living. From healthcare to communication, intelligent systems simplify daily proceedings remarkably. Public transportation systems are the most economical and ecofriendly systems, but they lack popularity in developing countries due to implementation inconsistencies. Here, we shall explore the impactful effects of AI on public transportation to birth intelligent transportation systems. This shall delve into cutting-edge systems like Lane Traffic Control and Automatic Passenger Counters. Integrating AI with transport sytems eases traffic control by providing resilient fleet management/operation systems to fleet managers and real-time information to the passengers to enhance the public transportation experience. Oyster cards in London, Electronic Toll Collection in Florida and TOPIS in Seoul have proved how groundbreaking AI has been in developed countries' public transports. Incorporating Intelligent Transport Systems in developing countries would evolve their traditional public transport systems and incline passengers towards public transport more, thus benefitting the economy, the environment and also themselves.
This session shall take the participants to a zoomed resolution to perceive the importance of intelligent transportation systems in the modern world and the benefits/challenges in implementing them from a non-Euclidean angle. Major systems demonstrating an intersection between AI, transport and communications engineering are to be discussed and technically/practically assessed for implementation purposes. Bus Management Systems, Vehicle enforcement systems and Smart city management systems also provide deeper insights to this power-packed session.

Add to agenda

Sanya Sinha

Beta Microsoft Learn Student Ambassador, Community Leader at VoC, Published Author

Read full bio

#NoMoreMatildas

till

Artificial Intelligence (AI) is the pinnacle of digitization; it is a technology that will revolutionize the way we work and live. With AI, we can develop models capable of understanding natural language and answering questions based on different data sources. In this talk we will present the development of a conversational agent, in Python, capable of answering questions about the legacy of women scientists. We will show how we collect data from Wikipedia and create our training data. We will also present how to re-train Huggin Face Deep Learning models with our own data, in this case related to the legacy of women scientists. Our motivation for this development is born due to the low percentage of female scientists (28.5%, according to UNESCO). This conversational agent acts as a natural language user interface to disseminate historical facts that show that women can have a great contribution in areas such as science and technology, motivating young women to follow the example of great figures in the history of the humanity.

Add to agenda

Carla Florida

associate researcher

Read full bio

Can a Machine Learning System Outperform Humans in Emotion Recognition?

till

In 1961, when Carl Sagan learned that a NASA spacecraft to Venus would carry no cameras, because the other scientists considered cameras to be excess weight, he insisted upon and campaigned for the chance to see the alien planet up close. In machine learning (ML)-based facial emotion recognition, is landmark-based training sufficient or does image-based training still have irreplaceable value? I believe that different facial representations can provide different, sometimes complementing views of emotions. When employed collectively, they enable a more reliable group emotion recognition. In this talk, I will first introduce my study of emotion recognition using image-trained ML model vs landmark-trained ML model in the context of a popular deepfake video. My experiment indicates that while the landmark-trained model performs better with articulated facial feature changes, the image-trained model outperforms on subtle facial expressions. Armed with these findings, we will take a tour of my adaptive group emotion recognition system for small discussion groups. After sharing some results using a collection of group discussion videos from YouTube, I will wrap up my talk by showing the benefits of an adaptive ML-based approach that automatically learns from both image and landmark facial representations and goes on to model group emotion dynamics, and augment individual emotion recognition.

Add to agenda

Valentina Zhang

Phillips Academy Exeter

Read full bio

Roundtable: Women in Data Science

till

In this roundtable session, you will hear opinions of several students and professionals on their path in data science.

Add to agenda

Ornella Altunyan

Cloud Developer Advocate, Microsoft

Locksley Kolakowski

Software Architect Analyst, Accenture

Anchal Bhalla

Senior Data Science Consultant at Capgemini

;