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Book Reviews – Mathematica Data Analysis

Book Reviews - Mathematica Data Analysis

Key Features

  • Use the power of Mathematica to analyze data in your applications
  • Discover the capabilities of data classification and pattern recognition offered by Mathematica
  • Use hundreds of algorithms for time series analysis to predict the future

Book Description

There are many algorithms for data analysis and it’s not always possible to quickly choose the best one for each case. Implementation of the algorithms takes a lot of time. With the help of Mathematica, you can quickly get a result from the use of a particular method, because this system contains almost all the known algorithms for data analysis.

If you are not a programmer but you need to analyze data, this book will show you the capabilities of Mathematica when just few strings of intelligible code help to solve huge tasks from statistical issues to pattern recognition. If you’re a programmer, with the help of this book, you will learn how to use the library of algorithms implemented in Mathematica in your programs, as well as how to write algorithm testing procedure.

With each chapter, you’ll be more immersed in the special world of Mathematica. Along with intuitive queries for data processing, we will highlight the nuances and features of this system, allowing you to build effective analysis systems.

With the help of this book, you will learn how to optimize the computations by combining your libraries with the Mathematica kernel.

What you will learn

  • Import data from different sources to Mathematica
  • Link external libraries with programs written in Mathematica
  • Classify data and partition them into clusters
  • Recognize faces, objects, text, and barcodes
  • Use Mathematica functions for time series analysis
  • Use algorithms for statistical data processing
  • Predict the result based on the observations

About the Author

Sergiy Suchok graduated in 2004 with honors from the Faculty of Cybernetics, Taras Shevchenko National University of Kyiv (Ukraine), and since then, he has a keen interest in information technology. He is currently working in the banking sector and has a PhD in Economics. Sergiy is the coauthor of more than 45 articles and has participated in more than 20 scientific and practical conferences devoted to economic and mathematical modeling.

1. First Steps in Data Analysis
System installation
Setting up the system
The Mathematica front end and kernel
Main features for writing expressions
2. Broad Capabilities for Data Import
Permissible data format for import
Importing data in Mathematica
Additional cleaning functions and data conversion
Checkpoint 2.1 – time for some practice!!!
Importing strings
Importing data from Mathematica’s notebooks
Controlling data completeness
3. Creating an Interface for an External Program
Wolfram Symbolic Transfer Protocol
Interface implementation with a program in С/С++
Calling Mathematica from C
Interacting with .NET programs
Interacting with Java
Interacting with R
4. Analyzing Data with the Help of Mathematica
Data clustering
Data classification
Image recognition
Recognizing faces
Recognizing text information
Recognizing barcodes
5. Discovering the Advanced Capabilities of Time Series
Time series in Mathematica
Mathematica’s information depository
Process models of time series
The moving average model
The autoregressive process – AR
The autoregression model – moving average (ARMA)
The seasonal integrated autoregressive moving-average process – SARIMA
Choosing the best time series process model
Tests on stationarity, invertibility, and autocorrelation
Checking for stationarity
Invertibility check
Autocorrelation check
6. Statistical Hypothesis Testing in Two Clicks
Hypotheses about the mean
Hypotheses about the variance
Checking the degree of sample dependence
Hypotheses on true sample distribution
7. Predicting the Dataset Behavior
Classical predicting
Image processing
Probability automaton modelling
8. Rock-Paper-Scissors – Intelligent Processing of Datasets
Interface development in Mathematica
Markov chains
Creating a portable demonstration

Book Reviews – Mathematica Data Analysis

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