Machine Learning Models and Algorithms for Big Data Classification: Thinking with Examples for Effective Learning
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
New York
Springer
2016
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| Schriftenreihe: | Integrated Series in Information Systems
36 |
| Schlagworte: | |
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| Beschreibung: | 1 Online-Ressource (XIX, 359 Seiten) 149 illus., 82 illus. in color |
| ISBN: | 9781489976413 |
| ISSN: | 2197-7968 |
| DOI: | 10.1007/978-1-4899-7641-3 |
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Datensatz im Suchindex
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| adam_text | MACHINE LEARNING MODELS AND ALGORITHMS FOR BIG DATA CLASSIFICATION
/ SUTHAHARAN, SHAN
: 2016
TABLE OF CONTENTS / INHALTSVERZEICHNIS
SCIENCE OF INFORMATION
PART I UNDERSTANDING BIG DATA
BIG DATA ESSENTIALS
BIG DATA ANALYTICS
PART II UNDERSTANDING BIG DATA SYSTEMS
DISTRIBUTED FILE SYSTEM
MAPREDUCE PROGRAMMING PLATFORM
PART III UNDERSTANDING MACHINE LEARNING
MODELING AND ALGORITHMS
SUPERVISED LEARNING MODELS
SUPERVISED LEARNING ALGORITHMS
SUPPORT VECTOR MACHINE
DECISION TREE LEARNING
PART IV UNDERSTANDING SCALING-UP MACHINE LEARNING
RANDOM FOREST LEARNING
DEEP LEARNING MODELS
CHANDELIER DECISION TREE
DIMENSIONALITY REDUCTION
DIESES SCHRIFTSTUECK WURDE MASCHINELL ERZEUGT.
MACHINE LEARNING MODELS AND ALGORITHMS FOR BIG DATA CLASSIFICATION
/ SUTHAHARAN, SHAN
: 2016
ABSTRACT / INHALTSTEXT
THIS BOOK PRESENTS MACHINE LEARNING MODELS AND ALGORITHMS TO ADDRESS BIG
DATA CLASSIFICATION PROBLEMS. EXISTING MACHINE LEARNING TECHNIQUES LIKE
THE DECISION TREE (A HIERARCHICAL APPROACH), RANDOM FOREST (AN ENSEMBLE
HIERARCHICAL APPROACH), AND DEEP LEARNING (A LAYERED APPROACH) ARE
HIGHLY SUITABLE FOR THE SYSTEM THAT CAN HANDLE SUCH PROBLEMS. THIS BOOK
HELPS READERS, ESPECIALLY STUDENTS AND NEWCOMERS TO THE FIELD OF BIG
DATA AND MACHINE LEARNING, TO GAIN A QUICK UNDERSTANDING OF THE
TECHNIQUES AND TECHNOLOGIES; THEREFORE, THE THEORY, EXAMPLES, AND
PROGRAMS (MATLAB AND R) PRESENTED IN THIS BOOK HAVE BEEN SIMPLIFIED,
HARDCODED, REPEATED, OR SPACED FOR IMPROVEMENTS. THEY PROVIDE VEHICLES
TO TEST AND UNDERSTAND THE COMPLICATED CONCEPTS OF VARIOUS TOPICS IN THE
FIELD. IT IS EXPECTED THAT THE READERS ADOPT THESE PROGRAMS TO
EXPERIMENT WITH THE EXAMPLES, AND THEN MODIFY OR WRITE THEIR OWN
PROGRAMS TOWARD ADVANCING THEIR KNOWLEDGE FOR SOLVING MORE COMPLEX AND
CHALLENGING PROBLEMS. THE PRESENTATION FORMAT OF THIS BOOK FOCUSES ON
SIMPLICITY, READABILITY, AND DEPENDABILITY SO THAT BOTH UNDERGRADUATE
AND GRADUATE STUDENTS AS WELL AS NEW RESEARCHERS, DEVELOPERS, AND
PRACTITIONERS IN THIS FIELD CAN EASILY TRUST AND GRASP THE CONCEPTS, AND
LEARN THEM EFFECTIVELY. IT HAS BEEN WRITTEN TO REDUCE THE MATHEMATICAL
COMPLEXITY AND HELP THE VAST MAJORITY OF READERS TO UNDERSTAND THE
TOPICS AND GET INTERESTED IN THE FIELD. THIS BOOK CONSISTS OF FOUR
PARTS, WITH THE TOTAL OF 14 CHAPTERS. THE FIRST PART MAINLY FOCUSES ON
THE TOPICS THAT ARE NEEDED TO HELP ANALYZE AND UNDERSTAND DATA AND BIG
DATA. THE SECOND PART COVERS THE TOPICS THAT CAN EXPLAIN THE SYSTEMS
REQUIRED FOR PROCESSING BIG DATA. THE THIRD PART PRESENTS THE TOPICS
REQUIRED TO UNDERSTAND AND SELECT MACHINE LEARNING TECHNIQUES TO
CLASSIFY BIG DATA. FINALLY, THE FOURTH PART CONCENTRATES ON THE TOPICS
THAT EXPLAIN THE SCALING-UP MACHINE LEARNING, AN IMPORTANT SOLUTION FOR
MODERN BIG DATA PROBLEMS
DIESES SCHRIFTSTUECK WURDE MASCHINELL ERZEUGT.
|
| any_adam_object | 1 |
| author | Suthaharan, Shan |
| author_GND | (DE-588)1089081995 |
| author_facet | Suthaharan, Shan |
| author_role | aut |
| author_sort | Suthaharan, Shan |
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| dewey-ones | 658 - General management |
| dewey-raw | 658 |
| dewey-search | 658 |
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| discipline | Informatik Wirtschaftswissenschaften |
| doi_str_mv | 10.1007/978-1-4899-7641-3 |
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| id | DE-604.BV043211991 |
| illustrated | Illustrated |
| indexdate | 2024-08-01T12:12:20Z |
| institution | BVB |
| isbn | 9781489976413 |
| issn | 2197-7968 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-028635129 |
| oclc_num | 930008298 |
| open_access_boolean | |
| owner | DE-2070s DE-1043 DE-Aug4 DE-573 DE-1049 DE-703 DE-473 DE-BY-UBG DE-29 DE-863 DE-BY-FWS DE-862 DE-BY-FWS DE-92 DE-739 DE-824 DE-M347 DE-898 DE-BY-UBR DE-634 DE-1046 DE-83 DE-859 DE-861 DE-523 DE-355 DE-BY-UBR DE-706 |
| owner_facet | DE-2070s DE-1043 DE-Aug4 DE-573 DE-1049 DE-703 DE-473 DE-BY-UBG DE-29 DE-863 DE-BY-FWS DE-862 DE-BY-FWS DE-92 DE-739 DE-824 DE-M347 DE-898 DE-BY-UBR DE-634 DE-1046 DE-83 DE-859 DE-861 DE-523 DE-355 DE-BY-UBR DE-706 |
| physical | 1 Online-Ressource (XIX, 359 Seiten) 149 illus., 82 illus. in color |
| psigel | ZDB-2-BUM ZDB-2-BUM_2016 |
| publishDate | 2016 |
| publishDateSearch | 2016 |
| publishDateSort | 2016 |
| publisher | Springer |
| record_format | marc |
| series | Integrated Series in Information Systems |
| series2 | Integrated Series in Information Systems |
| spellingShingle | Suthaharan, Shan Machine Learning Models and Algorithms for Big Data Classification Thinking with Examples for Effective Learning Integrated Series in Information Systems Business Management Database management Artificial intelligence Business and Management Artificial Intelligence (incl. Robotics) Künstliche Intelligenz Wirtschaft Datenauswertung (DE-588)4131193-0 gnd Big Data (DE-588)4802620-7 gnd Maschinelles Lernen (DE-588)4193754-5 gnd |
| subject_GND | (DE-588)4131193-0 (DE-588)4802620-7 (DE-588)4193754-5 |
| title | Machine Learning Models and Algorithms for Big Data Classification Thinking with Examples for Effective Learning |
| title_auth | Machine Learning Models and Algorithms for Big Data Classification Thinking with Examples for Effective Learning |
| title_exact_search | Machine Learning Models and Algorithms for Big Data Classification Thinking with Examples for Effective Learning |
| title_full | Machine Learning Models and Algorithms for Big Data Classification Thinking with Examples for Effective Learning Shan Suthaharan |
| title_fullStr | Machine Learning Models and Algorithms for Big Data Classification Thinking with Examples for Effective Learning Shan Suthaharan |
| title_full_unstemmed | Machine Learning Models and Algorithms for Big Data Classification Thinking with Examples for Effective Learning Shan Suthaharan |
| title_short | Machine Learning Models and Algorithms for Big Data Classification |
| title_sort | machine learning models and algorithms for big data classification thinking with examples for effective learning |
| title_sub | Thinking with Examples for Effective Learning |
| topic | Business Management Database management Artificial intelligence Business and Management Artificial Intelligence (incl. Robotics) Künstliche Intelligenz Wirtschaft Datenauswertung (DE-588)4131193-0 gnd Big Data (DE-588)4802620-7 gnd Maschinelles Lernen (DE-588)4193754-5 gnd |
| topic_facet | Business Management Database management Artificial intelligence Business and Management Artificial Intelligence (incl. Robotics) Künstliche Intelligenz Wirtschaft Datenauswertung Big Data Maschinelles Lernen |
| url | https://doi.org/10.1007/978-1-4899-7641-3 http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=028635129&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=028635129&sequence=000003&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA |
| volume_link | (DE-604)BV035421279 |
| work_keys_str_mv | AT suthaharanshan machinelearningmodelsandalgorithmsforbigdataclassificationthinkingwithexamplesforeffectivelearning |