Principles of data science:
Gespeichert in:
| Weitere Verfasser: | , , , , , |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Cham
Springer
[2020]
|
| Schriftenreihe: | Transactions on computational science and computational intelligence
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| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | xiv, 278 Seiten Illustrationen, Diagramme |
| ISBN: | 9783030439804 |
| ISSN: | 2569-7072 |
Internformat
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Datensatz im Suchindex
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| adam_text | Contents Simulation-Based Data Acquisition................................................................. Fabian Lorig and Ingo J. Timm Coding of Bits for Entities by Means of Discrete Events (CBEDE): A Method of Compression and Transmission of Data................................. Reinaldo Padilha França, Yuzo lano, Ana Carolina Borges Monteiro, and Rangel Arthur 1 17 Big Biomedical Data Engineering..................................................................... Ripon Patgiri and Sabuzima Nayak 31 Big Data Preprocessing: An Application on Online Social Networks........ Androniki Sapountzi and Kostas E. Psannis 49 Feature Engineering........................................................................................... Sorin Soviany and Cristina Soviany 79 Data Summarization Using Sampling Algorithms: Data Stream Case Study..................................................................... Rayane El Sibai, Jacques Bou Abdo, Yousra Chabchoub, Jacques Demerjian, Raja Chiky, and Kablan Barbar Fast Imputation: An Algorithmic Formalism................................................... Devisha Arunadevi Tiwari A Scientific Perspective on Big Data in Earth Observation........................ Corina Vaduva, Michele Iapaolo, and Mihai Datcu Visualizing High-Dimensional Data Using t-Distributed Stochastic Neighbor Embedding Algorithm........................................................................ Jayesh Soni, Nagarajan Prabakar, and Himanshu Upadhyay 125 155 189 IX
x Contents Active and Machine Learning for Earth Observation Image Analysis with Traditional and Innovative Approaches ................................. 207 Comeliu Octavian Dumitru, Gottfried Schwarz, Gabriel Dax, Vlad Andrei, Dongyang Ao, and Mihai Datcu Applications in Financial Industry: Use-Case for Fraud Management.... 233 Sorin Soviany and Cristina Soviany Stochastic Analysis for Short- and Long-Term Forecasting of Latin American Country Risk Indexes.................................................................. 249 Julián Pucheta, Gustavo Alasino, Carlos Salas, Martin Herrera, and Cristian Rodriguez Rivero Index.................................................................................................................. 273
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| adam_txt |
Contents Simulation-Based Data Acquisition. Fabian Lorig and Ingo J. Timm Coding of Bits for Entities by Means of Discrete Events (CBEDE): A Method of Compression and Transmission of Data. Reinaldo Padilha França, Yuzo lano, Ana Carolina Borges Monteiro, and Rangel Arthur 1 17 Big Biomedical Data Engineering. Ripon Patgiri and Sabuzima Nayak 31 Big Data Preprocessing: An Application on Online Social Networks. Androniki Sapountzi and Kostas E. Psannis 49 Feature Engineering. Sorin Soviany and Cristina Soviany 79 Data Summarization Using Sampling Algorithms: Data Stream Case Study. Rayane El Sibai, Jacques Bou Abdo, Yousra Chabchoub, Jacques Demerjian, Raja Chiky, and Kablan Barbar Fast Imputation: An Algorithmic Formalism. Devisha Arunadevi Tiwari A Scientific Perspective on Big Data in Earth Observation. Corina Vaduva, Michele Iapaolo, and Mihai Datcu Visualizing High-Dimensional Data Using t-Distributed Stochastic Neighbor Embedding Algorithm. Jayesh Soni, Nagarajan Prabakar, and Himanshu Upadhyay 125 155 189 IX
x Contents Active and Machine Learning for Earth Observation Image Analysis with Traditional and Innovative Approaches . 207 Comeliu Octavian Dumitru, Gottfried Schwarz, Gabriel Dax, Vlad Andrei, Dongyang Ao, and Mihai Datcu Applications in Financial Industry: Use-Case for Fraud Management. 233 Sorin Soviany and Cristina Soviany Stochastic Analysis for Short- and Long-Term Forecasting of Latin American Country Risk Indexes. 249 Julián Pucheta, Gustavo Alasino, Carlos Salas, Martin Herrera, and Cristian Rodriguez Rivero Index. 273 |
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| author_facet | Arabnia, Hamid R. 1958- Daimi, Kevin Stahlbock, Robert 1967- Soviany, Cristina Heilig, Leonard 1986- Brüssau, Kai 1972- |
| building | Verbundindex |
| bvnumber | BV046814597 |
| classification_rvk | QH 230 |
| ctrlnum | (OCoLC)1190910200 (DE-599)BVBBV046814597 |
| discipline | Wirtschaftswissenschaften |
| discipline_str_mv | Wirtschaftswissenschaften |
| format | Book |
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| id | DE-604.BV046814597 |
| illustrated | Illustrated |
| index_date | 2024-07-03T14:59:55Z |
| indexdate | 2024-07-10T08:54:35Z |
| institution | BVB |
| isbn | 9783030439804 |
| issn | 2569-7072 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-032223082 |
| oclc_num | 1190910200 |
| open_access_boolean | |
| owner | DE-355 DE-BY-UBR |
| owner_facet | DE-355 DE-BY-UBR |
| physical | xiv, 278 Seiten Illustrationen, Diagramme |
| publishDate | 2020 |
| publishDateSearch | 2020 |
| publishDateSort | 2020 |
| publisher | Springer |
| record_format | marc |
| series2 | Transactions on computational science and computational intelligence |
| spelling | Principles of data science Hamid R. Arabnia ; Kevin Daimi ; Robert Stahlbock ; Cristina Soviany ; Leonard Heilig ; Kai Brüssau (editors) Cham Springer [2020] xiv, 278 Seiten Illustrationen, Diagramme txt rdacontent n rdamedia nc rdacarrier Transactions on computational science and computational intelligence 2569-7072 Data Mining (DE-588)4428654-5 gnd rswk-swf Datenorganisation (DE-588)4214962-9 gnd rswk-swf Mustererkennung (DE-588)4040936-3 gnd rswk-swf Datenaufbereitung (DE-588)4148865-9 gnd rswk-swf Data Mining (DE-588)4428654-5 s Datenaufbereitung (DE-588)4148865-9 s Mustererkennung (DE-588)4040936-3 s Datenorganisation (DE-588)4214962-9 s DE-604 Arabnia, Hamid R. 1958- (DE-588)142843679 edt Daimi, Kevin (DE-588)1215127073 edt Stahlbock, Robert 1967- (DE-588)124295673 edt Soviany, Cristina (DE-588)1215127227 edt Heilig, Leonard 1986- (DE-588)1141098873 edt Brüssau, Kai 1972- (DE-588)123722209 edt Erscheint auch als Online-Ausgabe 978-3-030-43981-1 Digitalisierung UB Regensburg - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=032223082&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Principles of data science Data Mining (DE-588)4428654-5 gnd Datenorganisation (DE-588)4214962-9 gnd Mustererkennung (DE-588)4040936-3 gnd Datenaufbereitung (DE-588)4148865-9 gnd |
| subject_GND | (DE-588)4428654-5 (DE-588)4214962-9 (DE-588)4040936-3 (DE-588)4148865-9 |
| title | Principles of data science |
| title_auth | Principles of data science |
| title_exact_search | Principles of data science |
| title_exact_search_txtP | Principles of data science |
| title_full | Principles of data science Hamid R. Arabnia ; Kevin Daimi ; Robert Stahlbock ; Cristina Soviany ; Leonard Heilig ; Kai Brüssau (editors) |
| title_fullStr | Principles of data science Hamid R. Arabnia ; Kevin Daimi ; Robert Stahlbock ; Cristina Soviany ; Leonard Heilig ; Kai Brüssau (editors) |
| title_full_unstemmed | Principles of data science Hamid R. Arabnia ; Kevin Daimi ; Robert Stahlbock ; Cristina Soviany ; Leonard Heilig ; Kai Brüssau (editors) |
| title_short | Principles of data science |
| title_sort | principles of data science |
| topic | Data Mining (DE-588)4428654-5 gnd Datenorganisation (DE-588)4214962-9 gnd Mustererkennung (DE-588)4040936-3 gnd Datenaufbereitung (DE-588)4148865-9 gnd |
| topic_facet | Data Mining Datenorganisation Mustererkennung Datenaufbereitung |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=032223082&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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