This repository contains my code and presentation for my presentation, 'Machine Learning from Scratch', that I will be presenting on Friday, Sept. 21 2018, at the Devos Place in Grand Rapids, MI.
If you are watching this talk live and would like to participate in the coding demo, head to this repository
New to machine learning? This hands-on session will provide you with a foundational understanding of the basics of applied machine learning. We will cover how to frame ML problems, applications, and resources to learn more. You will be guided step-by-step in implementing an ML algorithm from scratch in Python. We will even analyze and make predictions on a Grand Rapids public dataset! This session is designed for those with no prior experience, though some programming experience and an introductory course in linear algebra and statistics would helpful. Many modern ML libraries can operate like a black box, accessible to those with no mathematical understanding of the algorithms. Our focus, however, will be on the mathematical constructs "under the hood" of the algorithm and on its practical implementation. Our intent is that this session provides you with a deep appreciation for the inner workings of ML algorithms and the direction to advance to more complex algorithms and other subsets of Artificial Intelligence.