This course explores how mathematics and computation are unified for reasoning about data and making discoveries about the world. The emphasis is on fundamentals of mathematics required for AI and machine learning. Topics include computational methods for solving systems of linear equations including matrix decompositions, analytic geometry, solutions of nonlinear equations, functions of two or more variables, partial derivatives, and gradient-based optimization including second-order methods.
This course explores how mathematics and computation are unified for reasoning about data and making discoveries about the world. The emphasis is on fundamentals of mathematics required for AI and machine learning. Topics include computational methods for solving systems of linear equations including matrix decompositions, analytic geometry, solutions of nonlinear equations, functions of two or more variables, partial derivatives, and gradient-based optimization including second-order methods.
