EderSantana/awesomeMLmath
Curated list to learn the math basics for machine learning
This is a curated collection of learning resources that helps aspiring machine learning practitioners, developers, and researchers build a strong mathematical foundation. It organizes external courses and materials on core topics like Calculus, Linear Algebra, Statistics, Probability, and Signal Processing. The end-user is anyone looking to understand the underlying math principles behind machine learning algorithms and models.
255 stars. No commits in the last 6 months.
Use this if you need to understand the fundamental mathematical concepts and theories that power machine learning, especially deep learning models.
Not ideal if you are looking for ready-to-use code, machine learning libraries, or practical project implementations without diving into the mathematical underpinnings.
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255
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MIT
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Last pushed
May 22, 2018
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