Steve Crow
Senior Software Engineer - NinjaCat
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Steve is a self-proclaimed Mathlete, and King of Snark. He is a lover of Greyhounds, twisty puzzles, and European Board Games. When not talking math to non-math people, and Java to non-Java people, he can be found sipping coffee and hacking on code.
The Magic of TypeScript
In this talk, you will learn how to harness the magic of TypeScript. Use its seer-like compiler to foretell errors before they happen. Delve into the charm of type narrowing and duck typing and use them to illuminate your code and banish the unknown. Whether new to TypeScript or a seasoned sage, all are welcome to come and learn to unlock the power of types.
Fractals: Recursion in Nature
How does one measure the coast of Great Britain? In the 1950s, Lewis Fry Richardson first noticed that countries' border measurements increase as the units get smaller. A decade later, Benoit Mandelbrot argued that the reason for this has to do with the "self-similarity" that coastlines have. Mandelbrot later used the word fractal from the Latin word fractus, meaning fragmented or broken, but he was not the first to observe self-similarity.
In 1883 George Cantor developed simple rules for generating an infinite set: start with a line, erase the middle third, and repeat again and again and again. The result of this creates another fractal, the Cantor middle thirds set.
In this talk, you will learn the history of fractals, various applications of fractals, and some code samples to generate images of fractals using recursive functions. No prior mathematical experience is necessary.
Data on Paper: From Punchcards to QR Codes
Before the early 1800s, producing intricate patterns in woven fabric was a laborious process. A weaver's assistant had to sit on top of the loom and manually raise and lower the threads. The invention of the Jacquard Machine revolutionized this process by using a series of interchangeable punchcards which held pattern weaving instructions.
In 1932 Wallace Flint wrote his master's thesis introducing a punchcard supermarket checkout system. Shoppers would collect punchcards that would be fed into the register, providing a more automated checkout experience. This idea, while it never came to fruition, ultimately led to the creation of the barcode.
From textiles to groceries and even computing, the desire for speed and automation has led to some fascinating ways to store data on paper. This talk will explore a selection of these ways, from punchcards, barcodes, QR Codes, and more.
Making Faces: Image Reduction and Recognition
A 350px by 300px image contains 105,000 individual pixels. Comparing each pixel to tell whether or not two images are the same is not efficient. What if we could reduce the number of features, while still maintaining patterns and trends? What if we could perform this recognition by only comparing 25 data points?
Principal Component Analysis is a standard method of extracting features from such a set of data.
This talk will show how Principal Component Analysis and the Singular Value Decomposition can be used to extract features from images of faces. With the ultimate goal to recognize the same face across different expressions and images.
Is This Your Card? Computer Vision for Playing Card Recognition
"Pick a card, any card," the magician prompts you fanning out a deck of cards. You select a card, note its value, and hand it back to the magician. They do some sleight of hand, make the card disappear into the deck, and then make it reappear. You confirm that it is, indeed, your original card. The magician moves on and you get to go back to enjoying your dinner.
Where is the real magic? Is it in the magician's ability to make a card reappear? Or, is it something that many of us take for granted each and every day? In the very instant you glance at a card, you're able to take in details without even thinking about it.
Computer Vision aims to teach computers to interact with the visual world. It has applications in navigation, automated inspection, medical image process, and so much more.
This talk will do the following:
- Introduce the field of Computer Vision.
- Demonstrate how to manipulate a webcam video feed and pre-process the video to perform Canny Edge Detection.
- Use these edges to isolate a playing card image and, eventually, identify which playing card is being shown.
No prior knowledge of Computer Vision or Machine Learning is necessary.
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