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Chapter 21 covers (1) constrained and unconstrained
optimization, (2) Lagrange multipliers, (3) linear, quadratic and
(general) non-linear programming, and (4) data denoising.
Stewardship
SOCR Resource, University of Michigan Rights
CC-BY Credits
SOCR, MIDAS, HBBS, DCMB, University of Michigan Creation Date
August 29th, 2017
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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…
Stewardship
SOCR Resource, University of Michigan Rights
CC-BY Credits
SOCR, MIDAS, HBBS, DCMB, University of Michigan Creation Date
August 1st, 2017
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DSPA Chapter 5 Dimensionality Reduction Dimensionality reduction techniques enable exploratory data analyses
by reducing the complexity of the dataset, still approximately
preserving important…
Stewardship
SOCR Resource, University of Michigan Rights
CC-BY Credits
SOCR, MIDAS, HBBS, DCMB, University of Michigan Creation Date
August 1st, 2017
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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,…
Stewardship
SOCR Resource, University of Michigan Rights
CC-BY Credits
SOCR, MIDAS, HBBS, DCMB, University of Michigan Creation Date
August 1st, 2017
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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…
Stewardship
SOCR Resource, University of Michigan Rights
CC-BY Credits
SOCR, MIDAS, HBBS, DCMB, University of Michigan Creation Date
August 1st, 2017
|
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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.…
Stewardship
SOCR Resource, University of Michigan Rights
CC-BY Credits
SOCR, MIDAS, HBBS, DCMB, University of Michigan Creation Date
August 1st, 2017
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