Mathematics in Machine Learning

Machine learning is fundamentally driven by mathematics, relying on four key areas: linear algebra, calculus, probability, and statistics. These mathematical concepts provide the theoretical framework for representing data, building models, and optimizing algorithms to learn from that data.

Available Tutorials

Tutorial	Posted	Views
How to Build a Linear Regression Model from Scratch Using Only NumPy and Matplotlib	Oct 17, 2025	101
The Complete Guide to Exploratory Data Analysis: From Theory to Practice	Oct 13, 2025	119
Understanding Underfitting and Overfitting in Machine Learning	Oct 08, 2025	104
Understanding Standard Deviation and Outliers with Bank Transaction Example	Sep 20, 2025	115
Gradient descent — mathematical explanation & full derivation	Sep 19, 2025	192
Derivation of the Softmax Function	Sep 18, 2025	126