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A GitHub repository implementing fundamental machine learning algorithms from scratch using plain NumPy, designed to help learners understand the inner workings of algorithms by focusing on clarity over performance. It covers supervised, unsupervised, deep learning, and reinforcement learning topics.
A GitHub repo offering build-from-scratch machine learning tutorials using NumPy, organized by categories, with an implementation-first approach.
The article compares two methods for normalizing RGB values (dividing by 255 vs 256) and explains the consequences for floating-point conversion and rounding, including uneven bin widths at the extremes.