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 |
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The Complete Guide to Exploratory Data Analysis: From Theory to Practice | Oct 13, 2025 | 16 |
Understanding Underfitting and Overfitting in Machine Learning | Oct 08, 2025 | 32 |
Understanding Standard Deviation and Outliers with Bank Transaction Example | Sep 20, 2025 | 28 |
Gradient descent — mathematical explanation & full derivation | Sep 19, 2025 | 91 |
Derivation of the Softmax Function | Sep 18, 2025 | 32 |