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Machine Learning and Data Science

Module 2

Functions and Graphs Used in Machine Learning

Module 3

Vectors and Geometric Representations of Data

Module 4

Matrices, Transformations, and Linear Systems

Module 5

Derivatives and Integrals for Modeling Change

Module 6

Multivariable Calculus and Numerical Optimization

Module 7

Probability Rules and Conditional Reasoning

Module 8

Random Variables and Probability Distributions

Module 9

Sampling, Uncertainty, and Statistical Inference

Module 10

The Mathematics of Linear Regression

Module 11

The Mathematics of Binary Classification

Module 12

Eigenvectors, Principal Components, and Dimensionality Reduction