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Beginning Mathematica and Wolfram for Data Science: Applications in Data Analysis, Machine Learning, and Neural Networks - Tapa blanda
Sinopsis
Enhance 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.
What You Will Learn
- Create datasets, work with data frames, and create tables
- Import, export, analyze, and visualize data
- Work with the Wolfram data repository
- Build reports on the analysis
- Use Mathematica for machine learning, with different algorithms, including linear, multiple, and logistic regression; decision trees; and data clustering
Who This Book Is For
Data scientists who are new to using Wolfram and Mathematica as a programming language or tool. Programmers should have some prior programming experience, but can be new to the Wolfram language.
"Sinopsis" puede pertenecer a otra edición de este libro.
Acerca del autor
Jalil Villalobos Alva is a Wolfram language programmer and Mathematica user. He graduated with a degree in engineering physics from the Universidad Iberoamericana in Mexico City. His research background comprises quantum physics, bionformatics, proteomics, and protein design. His academic interests cover the topics of quantum technology, bioinformatics, machine learning, artificial intelligence, stochastic processes, and space engineering. During his idle hours he likes to play soccer, swim, and listen to music.
De la contraportada
Enhance 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.
"Sobre este título" puede pertenecer a otra edición de este libro.
- EditorialApress
- Año de publicación2024
- ISBN 13 9798868803475
- EncuadernaciónTapa blanda
- IdiomaInglés
- Número de edición2
- Número de páginas488
- Contacto del fabricanteno disponible
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Beginning Mathematica and Wolfram for Data Science: Applications in Data Analysis, Machine Learning, and Neural Networks
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Beginning Mathematica and Wolfram for Data Science : Applications in Data Analysis, Machine Learning, and Neural Networks
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Beginning Mathematica and Wolfram for Data Science : Applications in Data Analysis, Machine Learning, and Neural Networks
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Beginning Mathematica and Wolfram for Data Science
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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Enhance 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 not Elektronisches Buch as a standard format, which also serves to create detailed reports of the processes carried out.What You Will LearnCreate datasets, work with data frames, and create tablesImport, export, analyze, and visualize dataWork with the Wolfram data repositoryBuild reports on the analysisUse Mathematica for machine learning, with different algorithms, including linear, multiple, and logistic regression; decision trees; and data clusteringWho This Book Is ForData scientists who are new to using Wolfram and Mathematica as a programming language or tool.Programmers should have some prior programming experience, but can be new to the Wolfram language. 488 pp. Englisch. Nº de ref. del artículo: 9798868803475
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Beginning Mathematica and Wolfram for Data Science
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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Enhance 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 i. Nº de ref. del artículo: 1488610532
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Beginning Mathematica and Wolfram for Data Science : Applications in Data Analysis, Machine Learning, and Neural Networks
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Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Enhance 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 not Elektronisches Buch as a standard format, which also serves to create detailed reports of the processes carried out.What You Will LearnCreate datasets, work with data frames, and create tablesImport, export, analyze, and visualize dataWork with the Wolfram data repositoryBuild reports on the analysisUse Mathematica for machine learning, with different algorithms, including linear, multiple, and logistic regression; decision trees; and data clusteringWho This Book Is ForData scientists who are new to using Wolfram and Mathematica as a programming language or tool.Programmers should have some prior programming experience, but can be new to the Wolfram language. Nº de ref. del artículo: 9798868803475
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