Mathematics
13 min
Probability for Machine Learning: Bayes & Distributions
Learn the probability behind machine learning: Bayes' theorem, key distributions, MLE and MAP, with worked examples and Python code you can run and check.
Xray AI Lab
Mathematics
Linear algebra, calculus, probability and optimization: the foundations behind the models.
Mathematics
15 min
Calculus for Machine Learning: Derivatives, Partial Derivatives, and Gradients
Learn derivatives visually, then see how partial derivatives and gradients drive neural-network training, with worked examples and verified Python code.
Mathematics
10 min
Gradient Descent Explained with Python: Math, Visualization, and Code
Learn how gradient descent minimizes a loss function. Derive the gradients, code it in NumPy, and test learning rates with a plotted experiment.
Mathematics
10 min
Linear Algebra for Machine Learning: Vectors, Matrices, and Eigenvalues (with NumPy)
Learn linear algebra for machine learning: vectors, dot products, matrix multiplication, and eigenvalues, with runnable NumPy examples and PCA.