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GitHub / JeffWang0325 / Microsoft-DAT256X-Essential-Math-for-Machine-Learning-Python-Edition

Machine learning and AI are built on mathematical principles like Calculus, Linear Algebra, Probability, Statistics, and Optimization. This course aims to help you learn some essential foundational concepts and the notation used to express them.

JSON API: http://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/JeffWang0325%2FMicrosoft-DAT256X-Essential-Math-for-Machine-Learning-Python-Edition

Stars: 6
Forks: 3
Open issues: 0

License: None
Language: Jupyter Notebook
Size: 2 MB
Dependencies parsed at: Pending

Created at: over 3 years ago
Updated at: about 1 year ago
Pushed at: over 3 years ago
Last synced at: 12 months ago

Topics: calculus, dat256x, data-science, data-visualization, gradient-descent, hypothesis-testing, linear-algebra, linear-regression, machine-learning, machine-learning-algorithms, matplotlib, microsoft, numpy, optimization, pandas-python, probability, probability-distribution, python, statistical-analysis, statistics

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