Machine Learning @ Devfest Edmonton 2022

Name: Machine Learning @ Devfest Edmonton 2022
Start: 2022-11-19T10:00:00-07:00
End: 2022-11-19T16:00:00-07:00
Location: University of Alberta

University of Alberta, Students Union Building, Orion Room (basement) 8900 114 St NW, Edmonton, AB, Edmonton, T6G 2J7

GDG Cloud Edmonton

DevFest is a global community-driven tech conference, hosted by the Google Developer Groups (GDG) community. Each DevFest event is crafted by its GDG organizers to fit the learning needs and interests of their local developer community, with a strong focus on knowledge exchange, networking, and learning about Google developer technologies.

Nov 19, 2022, 5:00 – 11:00 PM

128

RSVP'd

Key Themes

AICloudDevFestGoogle AssistantMachine LearningTensorFlowTensorFlow jsWomen Techmakers

About this event

What is DevFest ?
DevFest is a global community-driven tech conference, hosted by the Google Developer Groups (GDG) community. Each DevFest event is crafted by its GDG organizers to fit the learning needs and interests of their local developer community, with a strong focus on knowledge exchange, networking, and learning about Google developer technologies.
What to expect at AI/ML Edmonton DevFest 2022?Technical content
Worldwide events hosted by the Google Developer Groups community, featuring leading experts on Google technologies and Machine Learning
Talks
Full-day talks and insights on the latest development in AI/ML all centred on your favourite Google technologies.
Networking
Meet and connect with other developers and Google students club , Amii in your community.
To know more about Devfest and All Devests running around the world please visit this url : https://developers.google.com/community/devfest

J﻿oin our Slack group to hear latest updates and connect with group members.
Navigation to the Conference room 📍Students Union Building, Orion Room (basement) 8900 114 St NW, Edmonton, AB
Follow the signs in the campus and you will find our volunteers to help you navigate :)
Please bring your own Laptop you might require for the session.
Parking 🚗  There is public parking. It is not free. on the weekends it costs around $5.50 per day.
The best options for parking is Stadium carpark (covered). There are pay-stations to pay for parking, or you can use the Honk mobile app.
Check-in 🎫 Attendee check-in starts at 10.00 am First talk will be at 10:30am
For any query or concern regarding check-in/security please message us our GDG Cloud Edmonton slack group.
Ask for your name to attend Devfest event in the reception desk right after entering the conference room. 
Social media sharing:Feel free to share your event photo/video on social media
Use the hashtag #devfestEdmonton22
Tag our linkedin page Google Developer Group (GDG) Cloud Edmonton 
 and twitter account ( @GDG_Edmonton)
We will repost your post from our socials
Things to keep in mind:For any trouble, please message us in the slack group. Our team will be there to help you.
O﻿nly one check-in is allowed per email and name.
ConvenienceThere will be snacks, beverages, lunch, swags for you.
R﻿affle draws at the closing ceremony includes multiple prizes.
SPEAKERSC﻿heck all awesome conference speaker list here.
 If you have something awesome to share with the Edmonton tech community Submit your talk here for future events 
SPONSORSGDG Edmonton is a volunteer-driven group, dedicated to providing people of all skill levels free and low-cost access to professional networking and the opportunity to learn new technology skills in a variety of formats. We rely on sponsors to defray the costs of our events, such as speaker fees, educational material, catering, equipment rental, and advertising our events to reach more people in our community. 
Email:  gdg.cloud.edmonton@gmail.com to become a sponsor. We have many options for sponsorship
CALL FOR VOLUNTEERS﻿As a community-run event, event volunteers are critical to our success! We need volunteers all the way to help us in the in-person event. Please complete our volunteer interest form and we will be in touch soon!
COMMUNITY PARTNERSIf your community is willing to be a community partner of the devfest conference email us. Email us at:   gdg.cloud.edmonton@gmail.com 
C﻿ontact UsF﻿or any queries or concerns feel free to email us at: gdg.cloud.edmonton@gmail.com

When

Saturday, November 19, 2022
5:00 PM – 11:00 PM UTC

Where

University of Alberta
Students Union Building, Orion Room (basement) 8900 114 St NW, Edmonton, AB
Edmonton, T6G 2J7

Agenda

Door Opens - Welcoming and Registration
Mohammad Al-Ansari (Googler) - How to integrate Google Workspace with GCP AI/ML	Mohammad has been developing software for the last 18 years. Previously a Google Cloud Customer Engineer, he is now part of the Google Workspace Developer Relations team helping partners build add-ons and integrations for the platform. Mohammad will demonstrate how to train a custom text entity extraction model using Vertex AI AutoML, Cloud Vision API and BigQuery, and how to build a document workflow with the newly trained model and Google Workspace products (Drive/Gmail/Chat/Sheets).
Gautham Vasan (U of A) - using a mobile robot (Anki Vector) to illustrate some of the challenges of visuomotor policy learning	Vasan is a PhD candidate in Statistical Machine Learning at the University of Alberta. I work under the supervision of Rupam Mahmood with the Reinforcement Learning and Artificial Intelligence (RLAI) Group. I’m interested in building machines with human-like intelligence. My research lies in the overlapping areas of Artificial Intelligence and Robotics. I actively work on the design and development of Reinforcement Learning (RL) algorithms and continual learning systems for real-world robots. Humans have a remarkable ability to continually learn complicated concepts and exhibit intricate behaviors. We can learn new skills from only a few examples and quickly adapt to novel scenarios. To do so, we build upon our prior experience, reusing concepts, and abstractions that we've learned throughout our lives. While state-of-the-art applications of deep reinforcement learning (RL) have accomplished impressive feats, we humans acquire a commonsense understanding of the world using only a fraction of the data, time, and energy. The success of reinforcement learning (RL) for real-world robotics has been, in many instances, limited to carefully controlled, instrumented laboratory scenarios, often requiring arduous human effort and oversight to enable continuous learning. In this presentation, I’ll discuss the elements necessary for a robotic learning system that can continually and autonomously improve via interactions with the real world.
Fengdi Che (U of A) - Averaged Discount Factor Correction in the State Visitation Distribution	Fengdi is a A second-year P.h.D student under the supervision of professor Rupam Mahmood at the University of Alberta and gained her Master of Science and Computer Science degree at McGill University with professor Doina Precup. She works on policy gradient algorithms for reinforcement learning and shows interest in the task-agnostic objective for continual learning under non-stationary environments. The policy gradient theorem gives a convenient form of the policy gradient in terms of three factors: an action value, a gradient of the action likelihood, and a state distribution involving discounting called the discounted stationary distribution. But commonly used on-policy policy gradient estimators based on the policy gradient theorem account for the undiscounted state visitation distribution or the so-called stationary state distribution. Although these estimators work well on many tasks in practice, ignoring the discount factor in the state distribution may cause convergence to a sub-optimal policy. An existing solution corrects this discrepancy by including discount factor's powers in the gradient estimate. However, this solution is not widely adopted and does not work well in cases where the later states are similar to earlier states. We introduce a new way of accounting for the discounted stationary distribution that can be plugged in easily to many existing estimators to make them technically correct and of a lower variance than the existing correction. We empirically show on some OpenAI gym benchmarks that the inclusion of our corrective estimator can not only integrate information of early states along the whole trajectory but also filter out later distracting states. Thus, it avoids the performance degradation caused by the existing correction and shows improvement for some tasks.
Soft Drinks - Lunch and Networking Break
Community Keynote by Madusha ::: All about GDG Communities
R.G. (Randy) Goebel - Explainable Artificial Intelligence	R.G. (Randy) Goebel is currently professor of Computing Science in the Department of Computing Science at the University of Alberta and Fellow and co-founder of the Alberta Machine Intelligence Institute (Amii). He received the B.Sc. (Computer Science), M.Sc. (Computing Science), and Ph.D. (Computer Science) from the Universities of Regina, Alberta, and British Columbia, respectively. Professor Goebel's theoretical work on abduction, hypothetical reasoning and belief revision is internationally well known; his recent research is focused on the formalization of visualization and explainable artificial intelligence (XAI), especially in applications in autonomous driving, legal reasoning, and precision health. He has worked on optimization, algorithm complexity, systems biology, natural language processing, and automated reasoning. Randy has previously held faculty appointments at the University of Waterloo, University of Tokyo, Multimedia University (Kuala Lumpur), Hokkaido University (Sapporo), visiting researcher engagements at National Institute of Informatics (Tokyo), DFKI (Germany), and NICTA (Australia); he is actively involved in collaborative research projects in Canada, Japan, Germany, France, the UK, and China.
Christabel Wayllace - How AI agents can positively influence other's behavior	(Postdoctoral Fellow at the Intelligent Robot Learning Laboratory - University of Alberta) Christabel's interest is in studying the influence of human-agent-environment interaction and understanding how this interaction can benefit both humans and AI agents. She developed algorithms to use the environment's influence on an actor's behavior to facilitate goal recognition. Currently, she studies the influence of AI agents on human behavior.
Ekaba Bisong - Building Machine Learning Models with Tensor Flow	Ebeka is currently involved in in AI and ML Research. In addition, he maintains a relationship with the Intelligent Systems Labs at Carleton University with a research focus on Learning Systems (encompassing learning automata and reinforcement learning), Machine Learning, and Deep Learning.he is a Google Certified Professional Data Engineer, a Google Developer Expert in Machine Learning and author of the book “Building Machine Learning and Deep Learning Models on Google Cloud Platform” with Apress (Springer Nature) Publishers. This talk will provide an overview of reinforcement learning. The general goal of these approaches is to build an agent that maximizes rewards for a particular behaviour as the agent interacts with a random Environment in a feedback loop. The agent updates its policy or strategy for making decisions in the face of uncertainty by the responses the agent receives from the Environment. This talk will show examples of training agents in different Environments using the TensorFlow Agents library.
Madeleine (Maddie) Shang -Tools and repeatable roadmap for ML R&D success in industry.	AI Research @OpenMined - Federated Learning / RecSys Team Lead \|\| Founder - Data Science & ML @WomenWhoCode \|\| AI / Blockchain Researcher & Educator \|\| CFA L3 \|\| Adventurer.
Closing remarks and Raffle prize

Speakers

Randy Goebel

University of Alberta

Amii Co-founder - Professor of Computing Science

Mohammad Al-Ansari

Google

Google Workspace Developer Relations

Madusha Cooray

@ Google Developers

GDE Program Manager

Christabel Wayllace

University of Alberta

Postdoctoral Fellow at the Intelligent Robot Learning Laboratory

Ekaba Bisong

Google - SiliconBlast

Google Developer Expert - Principal Consultant & Research Scientist

Fengdi Che

University of Alberta

A second-year P.h.D student

Maddie Shang

OpenMined

Senior AI Research Engineer

Gautham Vasan

University of Alberta

A PhD candidate in Statistical Machine Learning

Facilitators

Yanqing Wu

University of Alberta

CS GSA

Vishwajeet Ohal

University of Alberta

CS GSA

XINLI CAI

Geospatial Cloud Developer

Natural Recources Canada

Shaimaa Abbas

Government of Alberta

GDG organizer - WTM Ambassador - System Analyst -

Rohan Saha

University of Alberta

PhD in computer science

Vannia Hnatiuk

GDG Cloud Edmonton | WTM Ambassador

Data Analyst

Sheila Schoepp

University of Alberta

CS GSA

Host

Sheila Schoepp

University of Alberta

CS GSA

Organizers

Xinli Cai

Canadian Centre for Mapping and Earth Observation

GDG Organizer

See bio

Rohan Saha

Event & Technical

See bio

Vannia Hnatiuk

GDG Cloud Edmonton

GDG Organizer

See bio

Devipriya Raju

University of Alberta

Co-organiser

See bio

Ndidi Obinwanne

Co - Organizer

See bio

Temitope Ajiboye

Jesta IS

Senior Flutter Developer

See bio

Contact Us

Machine Learning @ Devfest Edmonton 2022

Nov 19, 2022, 5:00 – 11:00 PM

Key Themes

About this event

What is DevFest ?

What to expect at AI/ML Edmonton DevFest 2022?

J﻿oin our Slack group to hear latest updates

and connect with group members.

Navigation to the Conference room 📍

Parking 🚗

Check-in 🎫

Social media sharing:

Things to keep in mind:

Convenience

SPEAKERS

SPONSORS

CALL FOR VOLUNTEERS﻿

COMMUNITY PARTNERS

C﻿ontact Us

When

Where

Agenda

Speakers

Randy Goebel

Mohammad Al-Ansari

Madusha Cooray

Christabel Wayllace

Ekaba Bisong

Fengdi Che

Maddie Shang

Gautham Vasan

Facilitators

Yanqing Wu

Vishwajeet Ohal

XINLI CAI

Shaimaa Abbas

Rohan Saha

Vannia Hnatiuk

Sheila Schoepp

Host

Sheila Schoepp

Partners

Google

Women Techmakers

Developer Student club

Amii

UA CSGSA

OpenHouse.ai

AlbertaAI

Organizers

Xinli Cai

Rohan Saha

Vannia Hnatiuk

Devipriya Raju

Ndidi Obinwanne

Temitope Ajiboye

Join our Slack group to hear latest updates

CALL FOR VOLUNTEERS

Contact Us