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Titolo: | Machine learning and data science : fundamentals and applications / / edited by Prateek Agrawal, Charu Gupta, Anand Sharma, Vishu Madaan and Nisheeth Joshi |
Pubblicazione: | Hoboken, NJ : , : Wiley |
Beverly, MA : , : Scrivener Publishing, , 2022 | |
©2022 | |
Descrizione fisica: | 1 online resource (271 pages) |
Disciplina: | 006.3/1 |
Soggetto topico: | Machine learning |
Data mining | |
Soggetto genere / forma: | Electronic books. |
Persona (resp. second.): | AgrawalPrateek |
GuptaCharu | |
SharmaAnand | |
MadaanVishu | |
JoshiNisheeth | |
Nota di bibliografia: | Includes bibliographical references and index. |
Nota di contenuto: | Cover -- Half-Title Page -- Title Page -- Copyright Page -- Contents -- Preface -- Book Description -- 1 Machine Learning: An Introduction to Reinforcement Learning -- 1.1 Introduction -- 1.1.1 Motivation -- 1.1.2 Machine Learning -- 1.1.3 How Machines Learn -- 1.1.4 Analogy -- 1.1.5 Reinforcement Learning Process -- 1.1.6 Reinforcement Learning Definitions: Basic Terminologies -- 1.1.7 Reinforcement Learning Concepts -- 1.2 Reinforcement Learning Paradigm: Characteristics -- 1.3 Reinforcement Learning Problem -- 1.4 Applications of Reinforcement Learning -- Conclusion -- References; 2 Data Analysis Using Machine Learning: An Experimental Study on UFC -- 2.1 Introduction -- 2.2 Proposed Methodology -- 2.2.1 Data Extraction: Preliminary -- 2.2.2 Pre-Processing Dataset -- 2.3 Experimental Evaluation and Visualization -- 2.4 Conclusion -- References -- 3 Dawn of Big Data with Hadoop and Machine Learning -- 3.1 Introduction -- 3.2 Big Data -- 3.2.1 The Life Cycle of Big Data -- 3.2.2 Challenges in Big Data -- 3.2.3 Scaling in Big Data Platforms -- 3.2.4 Factors to Understand Big Data Platforms and Their Selection Criteria -- 3.2.5 Current Trends in Big Data; 3.2.6 Big Data Use Cases -- 3.3 Machine Learning -- 3.3.1 Machine Learning Algorithms -- 3.4 Hadoop -- 3.4.1 Components of the Hadoop Ecosystem -- 3.4.2 Other Important Components of the Hadoop Ecosystem for Machine Learning -- 3.4.3 Benefits of Hadoop with Machine Learning -- 3.5 Studies Representing Applications of Machine Learning Techniques with Hadoop -- 3.6 Conclusion -- References -- 4 Industry 4.0: Smart Manufacturing in Industries The Future -- 4.1 Introduction -- Challenges or Responses -- Shared Infrastructure -- Security -- Costs or Profitability -- Future Proofing -- Conclusion; 6.3.3 Cluster-Based Mapping with Depth First Search (DFS) Algorithm -- 6.4 Proposed Methodology -- 6.4.1 Cluster-Based Mapping with FM Algorithm -- 6.4.2 Calculation of Total Power Consumption -- 6.4.3 Total Power Calculation by Using Tabu Search -- 6.5 Experimental Results and Discussion -- 6.5.1 Total Power Consumption in 2D NoC -- 6.5.2 Performance of Tabu Search for Power Optimization with Mesh Topology -- 6.5.3 Performance of Tabu Search for Power Optimization with Ring Topology -- 6.5.4 Average Hop Counts for 2D NoC -- 6.6 Conclusion -- References |
Titolo autorizzato: | Machine learning and data science |
ISBN: | 9781119776499 |
111977649X | |
9781119776482 | |
1119776481 | |
1-119-77649-X | |
1-119-77648-1 | |
Formato: | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione: | Inglese |
Record Nr.: | 9910585795503321 |
Lo trovi qui: | Univ. Federico II |
Opac: | Controlla la disponibilità qui |