Map/Reduce implementations of common ML algorithms

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Jupyter notebooks that cover how to implement from scratch different ML algorithms (ordinary least squares, gradient descent, k-means, alternating least squares), using Python NumPy, and how to then make these implementations scalable using Map/Reduce and Spark.

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Type Repository
SectionGitHub projects
Pricing open source
Platform Self-hosted
Systems исходный код
Site languageen
GitHubYannael/BigDataAnalytics_INFOH515

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Yannael/BigDataAnalytics_INFOH515

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