Introduction to Machine Learning with Feed-Forward Neural Networks
-Come join us to build a foundation in understanding how neural networks work, the math behind them and applicable use cases.
-We will cover how a neural network approximates arbitrary functions, how a neural network produces output, how a neural network learns and how to derive the math behind forward and backward propagation.
-It would be helpful to review your partial derivatives but is not necessary to gain a foundational understanding of neural networks.
In this talk, Abraham Kang will draw on his broad experience to help you identify neural networks work and how to forge your own path. Come with your questions, leave with a sense of purpose and direction!
6:30 pm - 7:00 pm Arrival and mingling
7:00 pm - 7:20 pm Opening words by Murat Baday, CEO of Magnimind Academy, the Meetup sponsors.
7:20 pm - 8:20 pm Abraham Kang, AI/ML Security Leader, Public Speaker, Motivator, Positive Catalyst and Mentor
8:20 pm - 9:00 pm Q&A
Abraham Kang is a professional public speaker and a security leader. He will talk about a neural network approximates arbitrary functions. Anyone who is related to data science or thinking to be a part of it, can come and join our friendly meetup.
We have special refreshments, pizza, beverages and promotions for the attendees.
About Abraham Kang:
Abraham Kang is fascinated with the nuanced details associated with programming languages and their associated APIs. Kang has a B.S. from Cornell University. He currently works for Samsung as a Senior Director Software helping to drive security and development in Samsung. Prior to joining Samsung, he worked as Principal Security Researcher for HP in their Software Security Research group.
Abraham is focused on AI/ML, application, framework, blockchain smart contracts, intelligent assistants, and mobile security and has presented his findings at Black Hat USA, DEFCON, OWASP AppSec USA, RSA, and BSIDES.