| Judul | Mathematics For Machine Learning / Marc Peter Deisenroth; A. Aldo Faisal; Cheng Soon Ong |
| Pengarang | Deisenroth, Marc Peter Faisal, A. Aldo Ong, Cheng Soon |
| EDISI | - |
| Penerbitan | New York : Cambridge University Press, 2021 |
| Deskripsi Fisik | xvii, 371p. :ill. ;25 Cm. |
| ISBN | 978-1-108-45514-5 |
| Subjek | MACHINE LEARNING - MATHEMATICS |
| Catatan | 357-366 Contents: I. Mathematical foundations 1. Introduction and motivation 2. Linear algebra 3. Analytic geometry 4. Matrix decompositions 5. Vector calculus 6. Probability and distributions 7. Continuous optimization II. Central machine learning problems 8. When models learning problems 9. Linear regression 10. Dimensionality reduction with principlal component analysis 11. Density estimation with gaussian mixture models 12. Classification with support vector machines |
| Bahasa | Inggris |
| Bentuk Karya | Bukan fiksi atau tidak didefinisikan |
| Target Pembaca | Umum |
| No Barcode | No. Panggil | Akses | Lokasi | Ketersediaan |
|---|---|---|---|---|
| 102623212 | 006.31 Dei m | Baca di tempat | Perpustakaan Pusat - KK KKC Koleksi Khusus |
Dipinjam |
| Tag | Ind1 | Ind2 | Isi |
| 001 | INLIS000000000152570 | ||
| 005 | 20230911030253 | ||
| 007 | ta | ||
| 008 | 230911################g##########0#eng## | ||
| 020 | # | # | $a 978-1-108-45514-5 |
| 035 | # | # | $a 0010-0923000156 |
| 082 | # | # | $a 006.31 |
| 084 | # | # | $a 006.31 Dei m |
| 100 | 1 | # | $a Deisenroth, Marc Peter |
| 245 | 1 | # | $a Mathematics For Machine Learning /$c Marc Peter Deisenroth; A. Aldo Faisal; Cheng Soon Ong |
| 250 | # | # | $a - |
| 260 | # | # | $a New York :$b Cambridge University Press,$c 2021 |
| 300 | # | # | $a xvii, 371p. : $b ill. ; $c 25 Cm. |
| 504 | # | # | $a 357-366 |
| 505 | # | # | $a Contents: I. Mathematical foundations 1. Introduction and motivation 2. Linear algebra 3. Analytic geometry 4. Matrix decompositions 5. Vector calculus 6. Probability and distributions 7. Continuous optimization II. Central machine learning problems 8. When models learning problems 9. Linear regression 10. Dimensionality reduction with principlal component analysis 11. Density estimation with gaussian mixture models 12. Classification with support vector machines |
| 650 | # | # | $a MACHINE LEARNING - MATHEMATICS |
| 700 | 1 | # | $a Faisal, A. Aldo |
| 700 | 1 | # | $a Ong, Cheng Soon |
| 990 | # | # | $a 102623212 |
| 990 | # | # | $a 102623212 |
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