Discrete Stochastic Processes Tools for Machine Learning and Data Science /
This text presents selected applications of discrete-time stochastic processes that involve random interactions and algorithms, and revolve around the Markov property. It covers recurrence properties of (excited) random walks, convergence and mixing of Markov chains, distribution modeling using phas...
Сохранить в:
| Главный автор: | |
|---|---|
| Соавтор: | |
| Формат: | Электронный ресурс eКнига |
| Язык: | английский |
| Опубликовано: |
Cham :
Springer Nature Switzerland : Imprint: Springer,
2024.
|
| Редактирование: | 1st ed. 2024. |
| Серии: | Springer Undergraduate Mathematics Series,
|
| Предметы: | |
| Online-ссылка: | https://doi.org/10.1007/978-3-031-65820-4 |
| Метки: |
Добавить метку
Нет меток, Требуется 1-ая метка записи!
|
MARC
| LEADER | 00000nam a22000005i 4500 | ||
|---|---|---|---|
| 001 | 978-3-031-65820-4 | ||
| 003 | DE-He213 | ||
| 005 | 20260906082107.0 | ||
| 007 | cr nn 008mamaa | ||
| 008 | 241008s2024 sz | o |||| 0|eng d | ||
| 020 | |a 9783031658204 |9 978-3-031-65820-4 | ||
| 024 | 7 | |a 10.1007/978-3-031-65820-4 |2 doi | |
| 050 | 4 | |a QA274-274.9 | |
| 072 | 7 | |a PBT |2 bicssc | |
| 072 | 7 | |a PBWL |2 bicssc | |
| 072 | 7 | |a MAT029040 |2 bisacsh | |
| 072 | 7 | |a PBT |2 thema | |
| 072 | 7 | |a PBWL |2 thema | |
| 082 | 0 | 4 | |a 519.23 |2 23 |
| 100 | 1 | |a Privault, Nicolas. |e author. |0 (orcid)0000-0003-4148-8543 |1 https://orcid.org/0000-0003-4148-8543 |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
| 245 | 1 | 0 | |a Discrete Stochastic Processes |h [electronic resource] : |b Tools for Machine Learning and Data Science / |c by Nicolas Privault. |
| 250 | |a 1st ed. 2024. | ||
| 264 | 1 | |a Cham : |b Springer Nature Switzerland : |b Imprint: Springer, |c 2024. | |
| 300 | |a 1 online resource (XII, 288 p. 144 illus.). |b 130 illus. in color. | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 341 | 0 | |b Table of contents navigation |2 onix | |
| 341 | 0 | |b Single logical reading order |2 onix | |
| 341 | 0 | |b Short alternative textual descriptions |2 onix | |
| 341 | 0 | |b Use of colour is Not sole means of conveying information |2 onix | |
| 341 | 0 | |b Use of high contrast between text and background colour |2 onix | |
| 341 | 0 | |b Next / Previous structural navigation |2 onix | |
| 341 | 0 | |b All Non-decorative content supports reading without sight |2 onix | |
| 347 | |a text file |b PDF |2 rda | ||
| 490 | 1 | |a Springer Undergraduate Mathematics Series, |x 2197-4144 | |
| 505 | 0 | |a - 1. A Summary of Markov Chains -- 2. Phase-Type Distributions -- 3. Synchronizing Automata -- 4. Random Walks and Recurrence -- 5. Cookie-Excited Random Walks -- 6. Convergence to Equilibrium -- 7. The Ising Model -- 8. Search Engines -- 9. Hidden Markov Model -- 10. Markov Decision Processes. | |
| 520 | |a This text presents selected applications of discrete-time stochastic processes that involve random interactions and algorithms, and revolve around the Markov property. It covers recurrence properties of (excited) random walks, convergence and mixing of Markov chains, distribution modeling using phase-type distributions, applications to search engines and probabilistic automata, and an introduction to the Ising model used in statistical physics. Applications to data science are also considered via hidden Markov models and Markov decision processes. A total of 32 exercises and 17 longer problems are provided with detailed solutions and cover various topics of interest, including statistical learning. | ||
| 532 | 8 | |a Accessibility summary: This PDF does Not fully comply with PDF/UA standards but does include limited screen reader support, descriptions for Non-text content (such as images and graphs), bookmarks for easy navigation, and searchable, selectable text. Users of assistive technologies may experience difficulty navigating or interpreting content in this document. We recognise the importance of accessibility and welcome queries about accessibility for any of our products. If you have a question or an access need, please get in touch with us via https://www.springernature.com/gp/info/accessibility | |
| 532 | 8 | |a Inaccessible, or known limited accessibility | |
| 532 | 8 | |a No reading system accessibility options actively disabled | |
| 532 | 8 | |a Publisher contact for further accessibility information: accessibilitysupport@springernature.com | |
| 588 | |a Print version record. | ||
| 650 | 0 | |a Stochastic processes. | |
| 650 | 0 | |a Computer science |x Mathematics. | |
| 650 | 1 | 4 | |a Stochastic Processes. |
| 650 | 2 | 4 | |a Mathematical Applications in Computer Science. |
| 710 | 2 | |a SpringerLink (Online service) | |
| 773 | 0 | |t Springer Nature eBook | |
| 776 | 0 | 8 | |i Printed edition: |z 9783031658198 |
| 776 | 0 | 8 | |i Printed edition: |z 9783031658211 |
| 830 | 0 | |a Springer Undergraduate Mathematics Series, |x 2197-4144 | |
| 856 | 4 | 0 | |u https://doi.org/10.1007/978-3-031-65820-4 |
| 912 | |a ZDB-2-SMA | ||
| 912 | |a ZDB-2-SXMS | ||
| 950 | |a Mathematics and Statistics (SpringerNature-11649) | ||
| 950 | |a Mathematics and Statistics (R0) (SpringerNature-43713) | ||