Statistical Packages

123

Solutions

294

Contributors

Statistical packages are software titles, such as JMP and GNU Octave, and programming languages, such as MATLAB, R and SAS, that are used to discover, explore and analyze data and suggest useful conclusions, either to learn something unexpected or to confirm a hypothesis. The field includes the design and analysis of techniques to give approximate but accurate solutions to hard problems in statistics, econometrics, time-series, optimization and 2D- and 3D-visualization. Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, in different business, science, and social science domains.

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The process of ML is comparable to data processing. Both systems search through information to appear for patterns. However, rather than extracting information for human comprehension as just in case of knowledge mining, ML uses that information to discover trends in data and alter program actions.
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Microsoft Azure 2017
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Microsoft Azure 2017

Azure has a changed a lot since it was originally introduce by adding new services and features. Do you know everything you need to about Azure? This course will teach you about the Azure App Service, monitoring and application insights, DevOps, and Team Services.

Why the R Programming Language Will Become Your Go To Language
When you discover the power of the R programming language, you are going to wonder how you ever lived without it! Learn why the language merits a place in your programming arsenal.
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Statistical Packages

123

Solutions

294

Contributors

Statistical packages are software titles, such as JMP and GNU Octave, and programming languages, such as MATLAB, R and SAS, that are used to discover, explore and analyze data and suggest useful conclusions, either to learn something unexpected or to confirm a hypothesis. The field includes the design and analysis of techniques to give approximate but accurate solutions to hard problems in statistics, econometrics, time-series, optimization and 2D- and 3D-visualization. Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, in different business, science, and social science domains.

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