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Awesome GitHub RepositoriesExpectation-Maximization Models
Statistical methods for finding maximum likelihood estimates of parameters in models with latent variables.
Distinguishing note: None of the provided candidates were relevant; this captures probabilistic clustering via latent parameter estimation.
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- eriklindernoren/ML-From-Scratch
eriklindernoren/ML-From-Scratch
30,849View on GitHubThis project is an educational toolkit that provides implementations of fundamental machine learning algorithms built from scratch. By avoiding high-level library abstractions, it serves as a pedagogical reference for understanding the mathematical foundations and core mechanics of supervised learning, unsupervised learning, and reinforcement learning models. The repository distinguishes itself through a modular approach to model construction, allowing users to build custom neural networks by chaining independent functional blocks. It covers a wide range of techniques, including gradient-base
Group data points by iteratively calculating membership probabilities to optimize the fit of statistical distributions to the data.
Pythondata-miningdata-sciencedeep-learning
