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Understanding and Building the Simplest Neural Network

Understanding and Building the Simplest Neural Network

Over the past year I’ve been reading and learning about neural networks, how they work, and how to use them. I’ve found the overwhelming majority of tutorials and introductions to NN either: a) focus on the math and derivations, or b) focus on the code and tools, but rarely seem to c) match the math 1:1 with the code. Both of these tutorial styles are often guilty of handwaving and simplifying the derivations, making it difficult for me to follow exactly how the math and code relate to each other.

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Introducing ClippingBezier: Find find intersecting points, paths, and shapes from UIBezierPath

Introducing ClippingBezier: Find find intersecting points, paths, and shapes from UIBezierPath

UIBezierPath’s an an incredibly powerful tool for modeling complex paths and shapes in Objective-C and Swift, but it’s surprisingly difficult to perform operations on two or more paths. Applications like PaintCode make it easy to get the difference or intersection between two paths, but there are limited options for doing this on demand in code. This is particularly meaningful in drawing apps like Loose Leaf, where all of the paths are generated by the user.

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Introducing JotUI: An Open Source OpenGL Drawing view for iOS

When I started working on Loose Leaf, I quickly realized that the hardest part of the app was finding a fast and efficient drawing UIView that I could add into my app. There were a fair number of tutorials that would solve the first 80%, but there was always some important pieces left as an exercise for the reader: Smooth curves, removing lag and stutter, or main-thread-blocking save/load.

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