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Matrix-Based Minimization   (Mathematica Guide)
 
Memory Measurement & Optimization   (Mathematica Guide)
 
Optimization   (Mathematica Guide)
Integrated into Mathematica is a full range of state-of-the-art local and global optimization techniques, both numeric and symbolic, including constrained nonlinear ...
Labeling Two-Dimensional Graphics   (Mathematica Tutorial)
Ways to label two-dimensional plots. Here is a plot, using the default Axes->True. Setting Frame->True generates a frame with axes, and removes tick marks from the ordinary ...
Function Visualization   (Mathematica Guide)
Long the standard for high-quality function and surface visualization, Mathematica incorporates a host of original numeric, symbolic, and geometric algorithms that automate ...
Options for Graphics   (Mathematica Tutorial)
When Mathematica plots a graph for you, it has to make many choices. It has to work out what the scales should be, where the function should be sampled, how the axes should ...
Representing Textual Forms by Boxes   (Mathematica Tutorial)
All textual and graphical forms in Mathematica are ultimately represented in terms of nested collections of boxes. Typically the elements of these boxes correspond to objects ...
Data Transforms and Smoothing   (Mathematica Guide)
Directly integrated into Mathematica's uniform architecture for handling lists of data is an array of highly optimized algorithms for transforming and smoothing datasets that ...
Version 6.0 added a collection of carefully optimized functions to Mathematica's powerful arsenal of numerical handling capabilities.
Statistical Data Analysis   (Mathematica Guide)
Mathematica integrates many aspects of statistical data analysis, from getting and exploring data to building high-quality models and and deducing consequences. Mathematica ...
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