Deep Learning Fast Start

• PLEASE BE SURE TO FILL THE FORM (https://goo.gl/forms/7UhgksBr5cPo1db02). RSVP to the Meetup DOES NOT guarantee you a place on the workshop. Only those who receive an email will be accepted to the workshop.*

This workshop will provide a gentle technical introduction to deep learning for the analytics leader and machine learning practitioner. Deep Learning, based on artificial neural networks, represents the fastest and most important area of AI-powered business transformation. We will walk through the principal technical concepts of deep learning, including hierarchical representation, forward and backward propagation, loss and cost function, and gradient descent. Participants should go away with a deep intuitive understanding of deep learning's technical underpinnings. The style of the workshop will be a combination of lecture and hands-on code and exercises. Prerequisites: familiarity with Python.

Attendance:

The workshop capacity is limited to 20 people. Please fill this form (https://goo.gl/forms/7UhgksBr5cPo1db02) to be considered for the workshop. Only those who fill the form and receive an email will be accepted to the workshop.

• PLEASE BE SURE TO FILL THE FORM (https://goo.gl/forms/7UhgksBr5cPo1db02). RSVP to the Meetup DOES NOT guarantee you a place on the workshop. Only those who receive an email will be accepted to the workshop.*

Agenda:

5.30pm-6.00pm - Networking and Dinner
6.00pm-8.00pm - Workshop
8.00pm-8.30pm - Wrap up and Networking

Instructor's bio:

Alfred Essa is Vice President, R&D and Analytics at McGraw-Hill Education where he has strategic responsibility for research, data science, and analytics. He has extensive experience in industry and academia, including serving as Chief Information Officer at MIT's Sloan School of Management and Director of Analytics Research & Strategy at Desire2Learn Inc. Alfred is an avid long-distance runner, having completed 7 marathons and qualified for the Boston marathon in 2010 with a time of 3:24. His most recent interest is developing free online tutorials for data analysis and scientific computing using the Python programming language.

Dr. Shirin Mojarad is currently a Lead Data Scientist at McGraw-Hill Education. She was formerly a senior analytics specialist in the Advanced Analytics team at Canadian Imperial Bank of Commerce (CIBC) and a data mining consultant with a leading software company in predictive analytics. Shirin’s expertise lies in drawing causal inferences in observational studies and applying machine learning to the field of causal inference, which she has applied at McGraw-Hill Education and published in international conferences. Shirin has led several workshops on Python, causal inference, and data mining in international conferences including Learning Analytics and Knowledge Conference, European Conference on Technology Enhanced Learning, Chief Data and Analytics Officer, and Big Data Summit.