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024 7 _a10.1007/979-8-8688-0348-2
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072 7 _aCOM051010
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100 1 _aVillalobos Alva, Jalil.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_980135
245 1 0 _aBeginning Mathematica and Wolfram for Data Science
_h[electronic resource] :
_bApplications in Data Analysis, Machine Learning, and Neural Networks /
_cby Jalil Villalobos Alva.
250 _a2nd ed. 2024.
264 1 _aBerkeley, CA :
_bApress :
_bImprint: Apress,
_c2024.
300 _aXXIII, 462 p. 368 illus., 308 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
505 0 _a1. Introduction to Mathematica -- 2. Data Manipulation -- 3. Working with Data and Datasets -- 4. Import and Export -- 5. Data Visualization -- 6. Statistical Data Analysis -- 7. Data Exploration -- 8. Machine Learning with the Wolfram Language -- 9. Neural Networks with the Wolfram Language -- 10. Neural Network Framework.
520 _aEnhance your data science programming and analysis with the Wolfram programming language and Mathematica, an applied mathematical tools suite. This second edition introduces the latest LLM Wolfram capabilities, delves into the exploration of data types in Mathematica, covers key programming concepts, and includes code performance and debugging techniques for code optimization. You’ll gain a deeper understanding of data science from a theoretical and practical perspective using Mathematica and the Wolfram Language. Learning this language makes your data science code better because it is very intuitive and comes with pre-existing functions that can provide a welcoming experience for those who use other programming languages. Existing topics have been reorganized for better context and to accommodate the introduction of Notebook styles. The book also incorporates new functionalities in code versions 13 and 14 for imported and exported data. You’ll see how to use Mathematica, where data management and mathematical computations are needed. Along the way, you’ll appreciate how Mathematica provides an entirely integrated platform: its symbolic and numerical calculation result in a mized syntax, allowing it to carry out various processes without superfluous lines of code. You’ll learn to use its notebooks as a standard format, which also serves to create detailed reports of the processes carried out. .
650 0 _aProgramming languages (Electronic computers).
_966206
650 0 _aArtificial intelligence
_xData processing.
650 0 _aMachine learning.
_955059
650 1 4 _aProgramming Language.
_966208
650 2 4 _aData Science.
650 2 4 _aMachine Learning.
_955059
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9798868803475
776 0 8 _iPrinted edition:
_z9798868803499
776 0 8 _iPrinted edition:
_z9798868810893
856 4 0 _uhttps://doi.org/10.1007/979-8-8688-0348-2
912 _aZDB-2-CWD
912 _aZDB-2-SXPC
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