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DSPA Chapter 21 Function Optimization

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

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DSPA Chapter 4 Linear Algebra and Matrix Computing

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

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DSPA Chapter 5 Dimensionality Reduction

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

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DSPA Chapter 10: SVM Classification

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

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DSPA Chapter 3 Data Visualization

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

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DSPA Chapter 9: Regression Classification

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.…

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