A Day with Machine Learning

GDG Cloud Vancouver
Sat, Apr 28, 2018, 9:00 AM (PDT)

About this event

New to Machine Learning but don’t know where to start? Join us for a Machine Learning Study Jam where we will run through the Machine Learning Crash Course (MLCC)!

This course is intended for those who wish to learn about ML from a practical, applied perspective that will enable you to use machine learning in your everyday projects and learn about the power of TensorFlow. This is a great opportunity for anyone with basic technical knowledge and limited Machine Learning knowledge willing to gain some practical experience in ML and TensorFlow.

We are delighted to have a special speaker on this event giving us a power talk on Machine Learning in E-Learning.

Speaker introduction:

Dr. Stella Lee (www.paradoxlearning.com) Dr. Lee has over 18 years of progressive experience internationally in consulting, planning, designing, implementing, and measuring learning initiatives. Today her focus is on large scale learning projects including enterprise-wide e-learning strategy and governance, learning management system (LMS) design, development, evaluation and implementation, educational software development, and learning analytics. She is passionate about augmenting technologies to optimize human potentials.

Talk: Machine Learning in Corporate E-learning - Some Applications and Trends

Abstract: In recent years, a lot of thoughts have been given on the future of organizational learning and some of the emerging trends and how they can be integrated as part of the overarching learning and development roadmap. Among them, Artificial Intelligence (AI) and Machine Learning is one of the hot topic in e-learning in the recent year. Indeed, intelligent and machine driven learning is forecasted to be the evolution of corporate learning by 2020. In this talk, I will present how machine learning algorithms can be applied in corporate e-learning, particularly in shaping the future design of learning management systems (LMS) to make them more flexible, adaptive, and learner-centric. Some examples will be provided to demonstrate how one can potentially track engagement of learners in real time; provide timely and adaptive feedback; and interact with employees using chat bots to address performance challenges.


08.30 am: Doors Open and Settle down
09:00 am - 09:30 am: Welcome and Introduction
09:30 am - 11:00 am: TensorFlow - Learning Machines
11.00 am - 12.15 pm: Machine Learning Crash Course (Part 1)
12.15 pm - 12.30 pm: Raffle
12.30 pm - 1.30 pm: Lunch Break
1.30 pm - 2.30 pm: Guest Talk by Dr. Stella Lee
2.30 pm - 2.45 pm: Raffle
2.45 pm - 3.45 pm: Machine Learning Crash Course (Part 2)
3.45 pm - 4.00 pm: Coffee and Networking break
4.00 pm - 4.45 pm: More Demos
4.45 pm - 5.00 pm: Closing Remarks by all organizers

Please note:
Lunch, Coffee, Snacks will be provided and yes there will be SWAGS !!!


Thank you Eventbase as our host and Google as our general sponsor.