AI, IoT, Big Data and Cloud Computing for Industry 4.0 / / edited by Amy Neustein, Parikshit N. Mahalle, Prachi Joshi, Gitanjali Rahul Shinde |
Autore | Neustein Amy |
Edizione | [1st ed. 2023.] |
Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023 |
Descrizione fisica | 1 online resource (589 pages) |
Disciplina | 658.40380285 |
Altri autori (Persone) |
MahalleParikshit N
JoshiPrachi ShindeGitanjali Rahul |
Collana | Signals and Communication Technology |
Soggetto topico |
Computational intelligence
Telecommunication Artificial intelligence Computational Intelligence Communications Engineering, Networks Artificial Intelligence |
ISBN | 3-031-29713-X |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Introduction -- Section 1: Fundamentals of the Industry 4.0 -- Fundamental of IoT -- Architecture of IoT -- Automation -- Big data challenges -- Cloud computing services -- convergence of IoT and cloud computing -- Section 2: Emerging trends in Artificial Intelligence -- Knowledge representation -- Machine learning -- Deep learning -- AI based industry automation -- Section 3: AI based data management, architecture and framework -- Algorithms and techniques for data management and cloud -- Reference architectures -- Frameworks for integrating IoT, ML and Cloud -- Section 4: Software Portability and Virtual Machine Design -- Virtual Machine designs -- VM design and programming-language/compiler theory concerns -- Section 5: Security for industry 4.0 -- Industry 4.0 -- Artificial intelligence -- Machine Learning -- Signal Processing -- Multimedia -- Big data -- Software Portability -- Virtual Machines -- Conclusion. . |
Record Nr. | UNINA-9910736004203321 |
Neustein Amy
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023 | ||
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Lo trovi qui: Univ. Federico II | ||
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Foundations of Data Science for Engineering Problem Solving |
Autore | Mahalle Parikshit Narendra |
Pubbl/distr/stampa | Singapore : , : Springer Singapore Pte. Limited, , 2021 |
Descrizione fisica | 1 online resource (125 pages) |
Altri autori (Persone) |
ShindeGitanjali Rahul
PisePriya Dudhale DeshmukhJyoti Yogesh |
Collana | Studies in Big Data Ser. |
Soggetto genere / forma | Electronic books. |
ISBN | 981-16-5160-4 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Intro -- Preface -- Contents -- About the Authors -- 1 Introduction to Data Science -- 1.1 What is Data Science? -- 1.2 Evolution with a Need for Data Science -- 1.3 Applications of Data Science -- 1.3.1 Use of Data Science in D-Mart (E-commerce and Retail Management) -- 1.3.2 Narrow Artificial Intelligence (AI) -- 1.3.3 Trustworthy Artificial Intelligence (AI) -- 1.4 Summary -- References -- 2 Data Collection and Preparation -- 2.1 Types of Data -- 2.2 Datasets -- 2.3 Taxonomy of Dataset -- 2.4 Statistical Perspective -- 2.5 Dataset Pre-processing -- 2.6 Data Cleaning -- 2.6.1 Handling Missing Values -- 2.6.2 Removing Noisy Data -- 2.7 Data Transformation -- 2.7.1 Normalization -- 2.7.2 Encoding -- 2.8 Data Reduction -- 2.8.1 Attribute Feature Selection -- 2.8.2 Dimensionality Reduction -- 2.8.3 Numerosity Reduction -- 2.9 Web Scrapping Tools -- 2.10 Summary -- References -- 3 Data Analytics and Learning Techniques -- 3.1 Data Analytics Overview -- 3.2 Machine Learning Approaches -- 3.2.1 Supervised Learning -- 3.2.2 Unsupervised Learning -- 3.2.3 Reinforcement Learning -- 3.3 Deep Learning Approaches -- 3.4 Data Science Roles -- References -- 4 Data Visualization Tools and Data Modelling -- 4.1 Need of Visualization of Data -- 4.1.1 Challenges of Data Visualization -- 4.1.2 Steps of Data Visualization -- 4.2 Visualization Tools -- 4.2.1 Importance of Usage of Tools for Visualization -- 4.2.2 MS Excel -- 4.2.3 Tableau -- 4.2.4 Matplotlib -- 4.2.5 Datawrapper -- 4.2.6 Microsoft PowerBI -- 4.3 Summary -- References -- 5 Data Science in Information, Communication and Technology -- 5.1 Introduction -- 5.2 Motivation -- 5.3 Case Study in Computer Engineering -- 5.3.1 To Choose Fastest Route to Reach Destination -- 5.3.2 To Get Food Recipe Recommendations of Our Interest -- 5.3.3 The Famous Netflix Case Study.
5.3.4 Case Study of Amazon Using Data Science -- 5.3.5 Case Study on KCC (Kisaan Call Center) -- 5.4 Summary -- References -- 6 Data Science in Civil Engineering and Mechanical Engineering -- 6.1 Introduction -- 6.2 Motivation -- 6.3 Case Studies in Civil Engineering -- 6.4 Case Studies in Mechanical Engineering -- 6.5 Summary -- References -- 7 Data Science in Clinical Decision System -- 7.1 Introduction -- 7.2 Motivation -- 7.3 Case Study in Clinical Decision System -- 7.3.1 Preventive Measures for Cardiovascular Disease Using Data Science -- 7.3.2 Case Study on COVID-19 Prediction -- 7.4 Summary -- References -- 8 Conclusions -- 8.1 Conclusions -- 8.2 Open Research Issues -- 8.3 Future Outlook -- References. |
Record Nr. | UNINA-9910497096203321 |
Mahalle Parikshit Narendra
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Singapore : , : Springer Singapore Pte. Limited, , 2021 | ||
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Lo trovi qui: Univ. Federico II | ||
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Predictive analytics for mechanical engineering : a beginner's guide / / by Parikshit N. Mahalle, Pravin P. Hujare, Gitanjali Rahul Shinde |
Autore | Mahalle Parikshit N. |
Pubbl/distr/stampa | Singapore : , : Springer, , [2023] |
Descrizione fisica | 1 online resource (107 pages) : illustrations |
Disciplina | 658.4038028563 |
Collana | SpringerBriefs in computational intelligence |
Soggetto topico |
Computational intelligence
Quantitative research Mechanical engineering Internet of things Computational Intelligence Data Analysis and Big Data Mechanical Engineering Internet of Things |
ISBN |
981-9948-50-9
9789819948505 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | 1. Introduction to Predictive Analytics -- 2. Data Acquisition and Preparation -- 3. Intelligent Approaches -- 4. Predictive Maintenance -- 5. Predictive Maintenance for Mechanical Design System -- 6. Predictive Maintenance for Manufacturing -- 7. Conclusions. |
Record Nr. | UNINA-9910741149603321 |
Mahalle Parikshit N.
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Singapore : , : Springer, , [2023] | ||
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Lo trovi qui: Univ. Federico II | ||
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