machine-learning-visualized and MachineLearning
These are **competitors** — both provide educational NumPy-based implementations of ML algorithms from scratch, targeting developers who want to understand algorithmic fundamentals rather than use production-ready libraries, so a user would typically choose one based on preference for either visualization-focused (A) or algorithm-focused (B) pedagogy.
About machine-learning-visualized
gavinkhung/machine-learning-visualized
ML algorithms implemented and derived from first-principles in Jupyter Notebooks and NumPy
This resource helps machine learning students and practitioners understand how core machine learning algorithms work. It provides interactive Jupyter Notebooks that visually demonstrate the training process of algorithms, showing how they learn and converge to optimal solutions. It's ideal for anyone looking to gain deeper intuition into ML algorithm mechanics.
About MachineLearning
carefree0910/MachineLearning
Machine learning algorithms implemented by pure numpy
This project offers fundamental machine learning algorithms built from scratch, primarily for those learning the underlying mechanics. It takes in raw numerical data, like spreadsheets or datasets, and helps you apply core machine learning models such as neural networks and support vector machines to understand how they work internally. It's designed for students or educators in data science and machine learning.
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