
Chapter 21 covers (1) constrained and unconstrained
optimization, (2) Lagrange multipliers, (3) linear, quadratic and
(general) nonlinear programming, and (4) data denoising.


DSPA Chapter 4 Linear Algebra and Matrix Computing Linear algebra is a branch of mathematics that studies linear
associations using vectors, vectorspaces, linear equations, linear
transformations…


DSPA Chapter 5 Dimensionality Reduction Dimensionality reduction techniques enable exploratory data analyses
by reducing the complexity of the dataset, still approximately
preserving important…


DSPA Chapter 10 SVM Classification In this chapter, we are going to cover two very powerful
machinelearning algorithms. These techniques have complex mathematical
formulations, however, efficient…


DSPA Chapter 3 Data Visualization In this chapter, we use a broad range of simulations and handson
activities to highlight some of the basic data visualization techniques
using R. A brief…


DSPA Chapter 9: Regression Classification In previous chapters (6, 7, and 8),
we covered some classification methods that use mathematical formalism
to address everyday life prediction problems.…
