Exploring NLP with Game of Thrones: Social Networks (1/2)
For this project, I wanted to explore the interactions between characters in the Game of Thrones Universe. Over the course of the show, relationships between characters change - friends become foes and aquaintances grow to form alliances. My goal for this project was to pick up on the changes in these relationships by using Social Network Analysis (SNA).Read On!
A Gentle Introduction to the Mathematics of Deep Learning: Functions and the Basis of Differential Calculus (1/2)
This is my third semester teaching differential calculus at the University of Arkansas, and if I'm being frank, I'm always extra disappointed in my ability to truly convey the importance of calculus. Finding myself in the intermediary realm between scientist, software engineer, and mathematician, I find the most appreciation for calculus in its sheer utility. Calculus is a tool, but a tool in the same way language is a tool. Just as language sets the foundation for practically all human interaction and expression, calculus has set a foundation for mathematical, scientific, and technological progress. It is practically impossible to exaggerate the value of calculus.
Budding engineers and scientists are usually tossed into introductory calculus and bombarded with rules and notation. Generally, a student’s first calculus course can be summarized as dreadful rote memorization in an attempt to stay afloat. While this blog post may not help you ace your calculus final, I'm hoping it does help you understand the value of learning calculus and provide you with the fundamentals for understanding machine learning concepts.Read On!
A Gentle Introduction to the Mathematics of Deep Learning: A Foreword?
Over the next couple of weeks, I'm going to give a minimal introduction to two of the key mathematical concepts required for understanding a large branch of machine learning algorithms - differential calculus and matrix algebra. After this, I'll have a post wrapping the two together (matrix calculus!) and explaining how these concepts are used in machine learning as a whole. Finally, I'll more specifically go into their use in deep learning algorithms such as neural networks.
I hoping more so than strictly providing a minimal introduction to calculus and matrices, I can get across the heart of these subjects so you can develop an appreciation for these fields. These posts will require a high-school introduction to algebra, but hopefully nothing more. Let's hope I'm not biting off more than I can chew with that statement!
Hey friend, thanks for checking out my site.
There's not much here yet, but I'm hoping this gives me a platform to discuss some more introductory machine learning concepts and possibly tie together some concepts you'll learn in my classes with "real-world" skills. Introductory math and science courses tend to act more like filters and less like siphons. I'm not sure that's the best approach to teaching, personally. I'll probably also discuss and contrast my experiences in academia and industry, and potentially highlight the ways they could learn from each other.
For now, here's a photo of my two cats Socrates and Kalliope when they were still kittens. They're pretty cool, and they love laying on my laptop, especially when I'm trying to get in a good coding sesh.