Section 3 chapters · 16 lessons
Math for ML
The math that actually shows up in machine learning — explained with numpy, code, and the geometric intuition that finally makes it click.
0 / 16 lessons
- 01
Linear Algebra
6 lessons - 01 Why linear algebra matters
- 02 Vectors
- 03 Matrices as transformations
- 04 Matrix multiplication
- 05 Eigenvalues & eigenvectors
- 06 PCA from scratch
- 02
Calculus
4 lessons - 07 Derivatives & tangents
- 08 Partial derivatives
- 09 Gradient descent
- 10 Backpropagation foundations
- 03
Probability & Statistics
6 lessons - 11 What is probability
- 12 Bayes theorem
- 13 Distributions you should know
- 14 Central limit theorem
- 15 Hypothesis testing
- 16 A/B testing