| 書目名稱 | Linear Algebra in Data Science |
| 編輯 | Peter Zizler,Roberta La Haye |
| 視頻video | http://file.papertrans.cn/587/586282/586282.mp4 |
| 概述 | Explores applications of linear algebra in data science, showing readers how the two are connected.Offers exercises that escalate in complexity, many of which incorporate MATLAB.Includes practice proj |
| 叢書名稱 | Compact Textbooks in Mathematics |
| 圖書封面 |  |
| 描述 | .This textbook explores applications of linear algebra in data science at an introductory level, showing readers how the two are deeply connected. The authors accomplish this by offering exercises that escalate in complexity, many of which incorporate MATLAB. Practice projects appear as well for students to better understand the real-world applications of the material covered in a standard linear algebra course. Some topics covered include singular value decomposition, convolution, frequency filtering, and neural networks. .Linear Algebra in Data Science. is suitable as a supplement to a standard linear algebra course.. |
| 出版日期 | Textbook 2024 |
| 關(guān)鍵詞 | Linear algebra; Data science; Neural networks; Wavelet transform; Linear algebra; Singular value decompos |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-031-54908-3 |
| isbn_softcover | 978-3-031-54907-6 |
| isbn_ebook | 978-3-031-54908-3Series ISSN 2296-4568 Series E-ISSN 2296-455X |
| issn_series | 2296-4568 |
| copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |
|Archiver|手機(jī)版|小黑屋|
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