Linear algebra with machine learning and data

著者

• Arangala, Crista

書誌事項

Linear algebra with machine learning and data

Crista Arangala

（Textbooks in mathematics）

CRC Press, 2023

1st ed

注記

Includes bibliographical references (p. 283-286) and index

内容説明・目次

内容説明

This textbook attempts to revolutionize the Advanced Linear Algebra course by offering the integration of data analysis through case studies. Many schools are trying to find ways to incorporate data analysis into the undergrad math curriculum. The author presents a real alternative to standard textbooks. The use of case studies to demonstrate how linear algebra can be used in data analysis separates this text from all others currently available from any major publisher.

目次

1 Graph Theory. 2. Stochastic Processes. 3. SVD and PCA. 4. Interpolation. 5. Optimization and Learning Techniques for Regression. 6. Decision Trees and Random Forests. 7. Random Matrices and Covariance Estimate. 8. Sample Solutions to Exercises.

「Nielsen BookData」 より

• NII書誌ID(NCID): BD02173854
• ISBN:
  • 9780367458393
• LCCN: 2022047264
• 出版国コード: us
• タイトル言語コード: eng
• 本文言語コード: eng
• 出版地: Boca Raton
• ページ数/冊数: xix, 289 p.
• 大きさ: 25 cm
• 分類:
  • LCC : QA184.2
• 件名:
  • LCSH : Algebras, Linear -- Textbook
  • LCSH : Machine learning -- Mathematics -- Textbooks
  • LCSH : Data mining -- Mathematics -- Textbooks
• 親書誌ID:
  • BA83550953