| 期刊全稱 | Beginning Mathematica and Wolfram for Data Science | | 期刊簡稱 | Applications in Data | | 影響因子2023 | Jalil Villalobos Alva | | 視頻video | http://file.papertrans.cn/193/192634/192634.mp4 | | 發(fā)行地址 | The first introduction to data science using Mathematica and Wolfram.Covers popular in-demand topics such as machine learning, neural networks, and new LLM functionalities.Includes freely available so | | 圖書封面 |  | | 影響因子 | .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 mi | | Pindex | Book 2024Latest edition |
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