Linear algebra for data science, machine learning, and signal processing (Record no. 9117)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 02862nam a2200229 4500 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20250507175623.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 250507b |||||||| |||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9781009418140 |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 512.5 |
| Item number | FES |
| 100 ## - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Fessler, Jeffrey A |
| 245 ## - TITLE STATEMENT | |
| Title | Linear algebra for data science, machine learning, and signal processing |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) | |
| Name of publisher, distributor, etc. | Cambridge University Press |
| Place of publication, distribution, etc. | New York |
| Date of publication, distribution, etc. | 2024 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | xviii, 431 p. |
| 365 ## - TRADE PRICE | |
| Price type code | GBP |
| Price amount | 49.99 |
| 500 ## - GENERAL NOTE | |
| General note | Table of contents:<br/>1 - Getting Started<br/><br/>pp 1-11<br/>2 - Introduction to Matrices<br/><br/>pp 12-62<br/>3 - Matrix Factorization: Eigendecomposition and SVD<br/><br/>pp 63-95<br/>4 - Subspaces, Rank, and Nearest-Subspace Classification<br/><br/>pp 96-142<br/>5 - Linear Least-Squares Regression and Binary Classification<br/><br/>pp 143-196<br/>6 - Norms and Procrustes Problems<br/><br/>pp 197-237<br/>7 - Low-Rank Approximation and Multidimensional Scaling<br/><br/>pp 238-282<br/>8 - Special Matrices, Markov Chains, and PageRank<br/><br/>pp 283-334<br/>9 - Optimization Basics and Logistic Regression<br/><br/>pp 335-364<br/>10 - Matrix Completion and Recommender Systems<br/><br/>pp 365-380<br/>11 - Neural Network Models<br/><br/>pp 381-389<br/>12 - Random Matrix Theory, Signal + Noise Matrices, and Phase Transitions<br/><br/>pp 390-404<br/><br/>[https://www.cambridge.org/highereducation/books/linear-algebra-for-data-science-machine-learning-and-signal-processing/1D558680AF26ED577DBD9C4B5F1D0FED#contents] |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. | Maximise student engagement and understanding of matrix methods in data-driven applications with this modern teaching package. Students are introduced to matrices in two preliminary chapters, before progressing to advanced topics such as the nuclear norm, proximal operators and convex optimization. Highlighted applications include low-rank approximation, matrix completion, subspace learning, logistic regression for binary classification, robust PCA, dimensionality reduction and Procrustes problems. Extensively classroom-tested, the book includes over 200 multiple-choice questions suitable for in-class interactive learning or quizzes, as well as homework exercises (with solutions available for instructors). It encourages active learning with engaging 'explore' questions, with answers at the back of each chapter, and Julia code examples to demonstrate how the mathematics is actually used in practice. A suite of computational notebooks offers a hands-on learning experience for students. This is a perfect textbook for upper-level undergraduates and first-year graduate students who have taken a prior course in linear algebra basics.<br/><br/>(https://www.cambridge.org/highereducation/books/linear-algebra-for-data-science-machine-learning-and-signal-processing/1D558680AF26ED577DBD9C4B5F1D0FED#contents) |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Linear algebra |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Data science |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Machine learning |
| 700 ## - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Nadakuditi, Raj Rao |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | Book |
| Source of classification or shelving scheme | Dewey Decimal Classification |
| Withdrawn status | Lost status | Source of classification or shelving scheme | Damaged status | Not for loan | Collection code | Bill No | Bill Date | Home library | Current library | Shelving location | Date acquired | Source of acquisition | Cost, normal purchase price | Total Checkouts | Full call number | Accession Number | Date last seen | Copy number | Cost, replacement price | Price effective from | Koha item type |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Dewey Decimal Classification | Operations Management & Quantitative Techniques | TB4774 | 21-03-2025 | Indian Institute of Management LRC | Indian Institute of Management LRC | General Stacks | 03/28/2025 | Technical Bureau India Pvt. Ltd. | 3616.53 | 512.5 FES | 008604 | 03/28/2025 | 1 | 5563.89 | 03/28/2025 | Book |