Machine learning refined: foundations, algorithms, and applications
Providing a unique approach to machine learning, this text contains fresh and intuitive, yet rigorous, descriptions of all fundamental concepts necessary to conduct research, build products, tinker, and play. By prioritizing geometric intuition, algorithmic thinking, and practical real world applica...
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| Main Authors: | , , |
|---|---|
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Cambridge
Cambridge University Press
2016
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| Subjects: | |
| Online Access: | UBT01 UER01 Volltext |
| Summary: | Providing a unique approach to machine learning, this text contains fresh and intuitive, yet rigorous, descriptions of all fundamental concepts necessary to conduct research, build products, tinker, and play. By prioritizing geometric intuition, algorithmic thinking, and practical real world applications in disciplines including computer vision, natural language processing, economics, neuroscience, recommender systems, physics, and biology, this text provides readers with both a lucid understanding of foundational material as well as the practical tools needed to solve real-world problems. With in-depth Python and MATLAB/OCTAVE-based computational exercises and a complete treatment of cutting edge numerical optimization techniques, this is an essential resource for students and an ideal reference for researchers and practitioners working in machine learning, computer science, electrical engineering, signal processing, and numerical optimization |
| Item Description: | Title from publisher's bibliographic system (viewed on 06 Sep 2016) |
| Physical Description: | 1 online resource (xiii, 286 pages) |
| ISBN: | 9781316402276 |
| DOI: | 10.1017/CBO9781316402276 |
Staff View
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| id | DE-604.BV043940076 |
| illustrated | Not Illustrated |
| indexdate | 2024-07-10T07:39:12Z |
| institution | BVB |
| isbn | 9781316402276 |
| language | English |
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| physical | 1 online resource (xiii, 286 pages) |
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| publishDate | 2016 |
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| publisher | Cambridge University Press |
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| spelling | Watt, Jeremy Verfasser (DE-588)1115509624 aut Machine learning refined foundations, algorithms, and applications Jeremy Watt, Reza Borhani, and Aggelos K. Katsaggelos Cambridge Cambridge University Press 2016 1 online resource (xiii, 286 pages) txt rdacontent c rdamedia cr rdacarrier Title from publisher's bibliographic system (viewed on 06 Sep 2016) Providing a unique approach to machine learning, this text contains fresh and intuitive, yet rigorous, descriptions of all fundamental concepts necessary to conduct research, build products, tinker, and play. By prioritizing geometric intuition, algorithmic thinking, and practical real world applications in disciplines including computer vision, natural language processing, economics, neuroscience, recommender systems, physics, and biology, this text provides readers with both a lucid understanding of foundational material as well as the practical tools needed to solve real-world problems. With in-depth Python and MATLAB/OCTAVE-based computational exercises and a complete treatment of cutting edge numerical optimization techniques, this is an essential resource for students and an ideal reference for researchers and practitioners working in machine learning, computer science, electrical engineering, signal processing, and numerical optimization Machine learning Künstliche Intelligenz (DE-588)4033447-8 gnd rswk-swf Maschinelles Lernen (DE-588)4193754-5 gnd rswk-swf Mensch-Maschine-Kommunikation (DE-588)4125909-9 gnd rswk-swf Kognitionswissenschaft (DE-588)4193780-6 gnd rswk-swf Künstliche Intelligenz (DE-588)4033447-8 s Maschinelles Lernen (DE-588)4193754-5 s Kognitionswissenschaft (DE-588)4193780-6 s Mensch-Maschine-Kommunikation (DE-588)4125909-9 s 1\p DE-604 Borhani, Reza Verfasser (DE-588)1115510444 aut Katsaggelos, Aggelos Konstantinos Verfasser aut Erscheint auch als Druck-Ausgabe 978-1-107-12352-6 https://doi.org/10.1017/CBO9781316402276 Verlag URL des Erstveröffentlichers Volltext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Watt, Jeremy Borhani, Reza Katsaggelos, Aggelos Konstantinos Machine learning refined foundations, algorithms, and applications Machine learning Künstliche Intelligenz (DE-588)4033447-8 gnd Maschinelles Lernen (DE-588)4193754-5 gnd Mensch-Maschine-Kommunikation (DE-588)4125909-9 gnd Kognitionswissenschaft (DE-588)4193780-6 gnd |
| subject_GND | (DE-588)4033447-8 (DE-588)4193754-5 (DE-588)4125909-9 (DE-588)4193780-6 |
| title | Machine learning refined foundations, algorithms, and applications |
| title_auth | Machine learning refined foundations, algorithms, and applications |
| title_exact_search | Machine learning refined foundations, algorithms, and applications |
| title_full | Machine learning refined foundations, algorithms, and applications Jeremy Watt, Reza Borhani, and Aggelos K. Katsaggelos |
| title_fullStr | Machine learning refined foundations, algorithms, and applications Jeremy Watt, Reza Borhani, and Aggelos K. Katsaggelos |
| title_full_unstemmed | Machine learning refined foundations, algorithms, and applications Jeremy Watt, Reza Borhani, and Aggelos K. Katsaggelos |
| title_short | Machine learning refined |
| title_sort | machine learning refined foundations algorithms and applications |
| title_sub | foundations, algorithms, and applications |
| topic | Machine learning Künstliche Intelligenz (DE-588)4033447-8 gnd Maschinelles Lernen (DE-588)4193754-5 gnd Mensch-Maschine-Kommunikation (DE-588)4125909-9 gnd Kognitionswissenschaft (DE-588)4193780-6 gnd |
| topic_facet | Machine learning Künstliche Intelligenz Maschinelles Lernen Mensch-Maschine-Kommunikation Kognitionswissenschaft |
| url | https://doi.org/10.1017/CBO9781316402276 |
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