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Sajiron

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Mathematical Foundations for Machine Learning in JavaScript

Machine Learning might sound complex, but at its core, it's powered by math. Whether it's calculating gradients, scaling vectors, or multiplying matrices, having a solid grasp of the underlying mathematics can take you from just using models to truly understanding them.

In this blog, I break down the core mathematical concepts that form the foundation of ML:

๐Ÿ“ Scalars, Vectors, and Matrices

โž• Vector Operations and Dot Product

โœ–๏ธ Matrix Multiplication

๐Ÿงฎ Derivatives and Gradient Descent

๐Ÿ“Š Probability & Statistics essentials
All explained in a beginner-friendly way using JavaScript, so you can immediately try things out as you learn.

This post is perfect for:

JavaScript developers curious about ML

Beginners looking to understand the โ€œwhyโ€ behind the math

Anyone who prefers learning by coding instead of just theory

๐Ÿ”— Read the full blog here:
๐Ÿ‘‰ Mathematical Foundations for Machine Learning in JavaScript

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