World of Business with Data and Analytics:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Singapore
Springer
2022
|
| Ausgabe: | 1st ed |
| Schriftenreihe: | Studies in Autonomic, Data-Driven and Industrial Computing Series
|
| Schlagworte: | |
| Online-Zugang: | HWR01 |
| Beschreibung: | Description based on publisher supplied metadata and other sources |
| Beschreibung: | 1 Online-Ressource (211 Seiten) |
| ISBN: | 9789811956898 |
Internformat
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| 505 | 8 | |a Intro -- Preface -- Acknowledgements -- Contents -- About the Editors -- 1 Dynamic Demand Planning for Distorted Historical Data Due to Pandemic -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 4 Results -- 5 Conclusion -- References -- 2 Cognitive Models to Predict Pipeline Leaks and Ruptures -- 1 Introduction -- 2 Literature Review -- 3 Material and Methodology -- 3.1 Defining the Solution Using Data and Analytics -- 4 Results -- 5 Conclusion -- References -- 3 Network Optimization of the Electricity Grid to Manage Distributed Energy Resources Using Data and Analytics -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Defining a Network Optimization Solution to Build an Agile Grid -- 3.2 Defining the Problem -- 3.3 Defining a Solution for the Problem -- 4 Results -- 5 Conclusion -- References -- 4 Enhancing Market Agility Through Accurate Price Indicators Using Contextualized Data Analytics -- 1 Introduction -- 2 Literature Review -- 3 Data-Flow in Utility Value Chain -- 4 Handaling Market data Volatility and Coherency -- 5 Leveraging Data Analytics in Improving Accuracy of Price-Prediction Models -- 6 Data-Reliant Congestion Management -- 7 Unlocking Techno Commercial Benefits to Utility -- 8 Conclusion -- References -- 5 Infrastructure for Automated Surface Damage Classification and Detection in Production Industries Using ResUNet-based Deep Learning Architecture -- 1 Introduction -- 2 Literature Review -- 3 Dataset Description -- 4 Methodology -- 4.1 Two-Phase Learning Approach -- 5 Results -- 6 Conclusion -- References -- 6 Cardiac Arrhythmias Classification and Detection for Medical Industry Using Wavelet Transformation and Probabilistic Neural Network Architecture -- 1 Introduction -- 2 Literature Review -- 3 The Solution -- 3.1 Discrete Wavelet Transformation -- 3.2 Probabilistic Neural Network | |
| 505 | 8 | |a 4 Experimental Outcome -- 5 Results and Discussion -- 6 Conclusion -- References -- 7 Investor Behavior Towards Mutual Fund -- 1 Introduction -- 2 Literature Review -- 3 Materials and Methods -- 4 Experimental Result and Evaluation -- 5 Results and Discussions -- 6 Conclusion and Future Scope -- References -- 8 iMask-An Artificial Intelligence Based Redaction Engine -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 4 Results -- 5 Conclusion -- References -- 9 Intrusion Detection System Using Signature-Based Detection and Data Mining Technique -- 1 Introduction -- 2 Literature Review -- 3 Materials and Methods -- 4 Experimental Result and Evaluation -- 5 Conclusion -- References -- 10 Cloud Cost Intelligence Using Machine Learning -- 1 Introduction -- 2 Literature Review -- 3 Materials and Methods -- 4 Results and Recommendations -- 5 Conclusion -- References -- 11 Mining Deeper Insights from Texts Using Unsupervised NLP -- 1 Introduction -- 2 Literature Review -- 3 Materials and Methods -- 4 Result -- 5 Conclusion -- References -- 12 Explainable AI for ML Ops -- 1 Introduction -- 1.1 ML and The "Last Mile" Problem -- 1.2 Keeping Tabs on the Model -- 1.3 Explainable AI for Model Monitoring -- 2 Literature Review -- 2.1 AI/ML Maturity -- 2.2 Rise of ML Ops -- 2.3 ML Ops in Postproduction -- 3 Materials and Methods -- 3.1 Datasets -- 3.2 Explainable AI 101 -- 3.3 Explainability and ML Monitoring -- 4 Exploratory Data Analysis -- 5 Experimental Analysis -- 6 Results -- 6.1 SOLUTION 1: Local Explanation with One Particular Observation -- 6.2 SOLUTION 2: Global Monitoring: Iterating the Model 100 Times, Introduce the Manipulation from the 30th Iteration -- 7 Conclusion -- References | |
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Datensatz im Suchindex
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| author | Sharma, Neha |
| author_facet | Sharma, Neha |
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| building | Verbundindex |
| bvnumber | BV049408642 |
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| contents | Intro -- Preface -- Acknowledgements -- Contents -- About the Editors -- 1 Dynamic Demand Planning for Distorted Historical Data Due to Pandemic -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 4 Results -- 5 Conclusion -- References -- 2 Cognitive Models to Predict Pipeline Leaks and Ruptures -- 1 Introduction -- 2 Literature Review -- 3 Material and Methodology -- 3.1 Defining the Solution Using Data and Analytics -- 4 Results -- 5 Conclusion -- References -- 3 Network Optimization of the Electricity Grid to Manage Distributed Energy Resources Using Data and Analytics -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Defining a Network Optimization Solution to Build an Agile Grid -- 3.2 Defining the Problem -- 3.3 Defining a Solution for the Problem -- 4 Results -- 5 Conclusion -- References -- 4 Enhancing Market Agility Through Accurate Price Indicators Using Contextualized Data Analytics -- 1 Introduction -- 2 Literature Review -- 3 Data-Flow in Utility Value Chain -- 4 Handaling Market data Volatility and Coherency -- 5 Leveraging Data Analytics in Improving Accuracy of Price-Prediction Models -- 6 Data-Reliant Congestion Management -- 7 Unlocking Techno Commercial Benefits to Utility -- 8 Conclusion -- References -- 5 Infrastructure for Automated Surface Damage Classification and Detection in Production Industries Using ResUNet-based Deep Learning Architecture -- 1 Introduction -- 2 Literature Review -- 3 Dataset Description -- 4 Methodology -- 4.1 Two-Phase Learning Approach -- 5 Results -- 6 Conclusion -- References -- 6 Cardiac Arrhythmias Classification and Detection for Medical Industry Using Wavelet Transformation and Probabilistic Neural Network Architecture -- 1 Introduction -- 2 Literature Review -- 3 The Solution -- 3.1 Discrete Wavelet Transformation -- 3.2 Probabilistic Neural Network 4 Experimental Outcome -- 5 Results and Discussion -- 6 Conclusion -- References -- 7 Investor Behavior Towards Mutual Fund -- 1 Introduction -- 2 Literature Review -- 3 Materials and Methods -- 4 Experimental Result and Evaluation -- 5 Results and Discussions -- 6 Conclusion and Future Scope -- References -- 8 iMask-An Artificial Intelligence Based Redaction Engine -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 4 Results -- 5 Conclusion -- References -- 9 Intrusion Detection System Using Signature-Based Detection and Data Mining Technique -- 1 Introduction -- 2 Literature Review -- 3 Materials and Methods -- 4 Experimental Result and Evaluation -- 5 Conclusion -- References -- 10 Cloud Cost Intelligence Using Machine Learning -- 1 Introduction -- 2 Literature Review -- 3 Materials and Methods -- 4 Results and Recommendations -- 5 Conclusion -- References -- 11 Mining Deeper Insights from Texts Using Unsupervised NLP -- 1 Introduction -- 2 Literature Review -- 3 Materials and Methods -- 4 Result -- 5 Conclusion -- References -- 12 Explainable AI for ML Ops -- 1 Introduction -- 1.1 ML and The "Last Mile" Problem -- 1.2 Keeping Tabs on the Model -- 1.3 Explainable AI for Model Monitoring -- 2 Literature Review -- 2.1 AI/ML Maturity -- 2.2 Rise of ML Ops -- 2.3 ML Ops in Postproduction -- 3 Materials and Methods -- 3.1 Datasets -- 3.2 Explainable AI 101 -- 3.3 Explainability and ML Monitoring -- 4 Exploratory Data Analysis -- 5 Experimental Analysis -- 6 Results -- 6.1 SOLUTION 1: Local Explanation with One Particular Observation -- 6.2 SOLUTION 2: Global Monitoring: Iterating the Model 100 Times, Introduce the Manipulation from the 30th Iteration -- 7 Conclusion -- References |
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| dewey-full | 658.4030028563 |
| dewey-hundreds | 600 - Technology (Applied sciences) |
| dewey-ones | 658 - General management |
| dewey-raw | 658.4030028563 |
| dewey-search | 658.4030028563 |
| dewey-sort | 3658.4030028563 |
| dewey-tens | 650 - Management and auxiliary services |
| discipline | Wirtschaftswissenschaften |
| discipline_str_mv | Wirtschaftswissenschaften |
| edition | 1st ed |
| format | Electronic eBook |
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| id | DE-604.BV049408642 |
| illustrated | Not Illustrated |
| index_date | 2024-07-03T23:05:37Z |
| indexdate | 2024-07-10T10:06:17Z |
| institution | BVB |
| isbn | 9789811956898 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-034735726 |
| oclc_num | 1346986780 |
| open_access_boolean | |
| owner | DE-2070s |
| owner_facet | DE-2070s |
| physical | 1 Online-Ressource (211 Seiten) |
| psigel | ZDB-30-PQE ZDB-30-PQE HWR_PDA_PQE |
| publishDate | 2022 |
| publishDateSearch | 2022 |
| publishDateSort | 2022 |
| publisher | Springer |
| record_format | marc |
| series2 | Studies in Autonomic, Data-Driven and Industrial Computing Series |
| spelling | Sharma, Neha Verfasser aut World of Business with Data and Analytics 1st ed Singapore Springer 2022 ©2022 1 Online-Ressource (211 Seiten) txt rdacontent c rdamedia cr rdacarrier Studies in Autonomic, Data-Driven and Industrial Computing Series Description based on publisher supplied metadata and other sources Intro -- Preface -- Acknowledgements -- Contents -- About the Editors -- 1 Dynamic Demand Planning for Distorted Historical Data Due to Pandemic -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 4 Results -- 5 Conclusion -- References -- 2 Cognitive Models to Predict Pipeline Leaks and Ruptures -- 1 Introduction -- 2 Literature Review -- 3 Material and Methodology -- 3.1 Defining the Solution Using Data and Analytics -- 4 Results -- 5 Conclusion -- References -- 3 Network Optimization of the Electricity Grid to Manage Distributed Energy Resources Using Data and Analytics -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Defining a Network Optimization Solution to Build an Agile Grid -- 3.2 Defining the Problem -- 3.3 Defining a Solution for the Problem -- 4 Results -- 5 Conclusion -- References -- 4 Enhancing Market Agility Through Accurate Price Indicators Using Contextualized Data Analytics -- 1 Introduction -- 2 Literature Review -- 3 Data-Flow in Utility Value Chain -- 4 Handaling Market data Volatility and Coherency -- 5 Leveraging Data Analytics in Improving Accuracy of Price-Prediction Models -- 6 Data-Reliant Congestion Management -- 7 Unlocking Techno Commercial Benefits to Utility -- 8 Conclusion -- References -- 5 Infrastructure for Automated Surface Damage Classification and Detection in Production Industries Using ResUNet-based Deep Learning Architecture -- 1 Introduction -- 2 Literature Review -- 3 Dataset Description -- 4 Methodology -- 4.1 Two-Phase Learning Approach -- 5 Results -- 6 Conclusion -- References -- 6 Cardiac Arrhythmias Classification and Detection for Medical Industry Using Wavelet Transformation and Probabilistic Neural Network Architecture -- 1 Introduction -- 2 Literature Review -- 3 The Solution -- 3.1 Discrete Wavelet Transformation -- 3.2 Probabilistic Neural Network 4 Experimental Outcome -- 5 Results and Discussion -- 6 Conclusion -- References -- 7 Investor Behavior Towards Mutual Fund -- 1 Introduction -- 2 Literature Review -- 3 Materials and Methods -- 4 Experimental Result and Evaluation -- 5 Results and Discussions -- 6 Conclusion and Future Scope -- References -- 8 iMask-An Artificial Intelligence Based Redaction Engine -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 4 Results -- 5 Conclusion -- References -- 9 Intrusion Detection System Using Signature-Based Detection and Data Mining Technique -- 1 Introduction -- 2 Literature Review -- 3 Materials and Methods -- 4 Experimental Result and Evaluation -- 5 Conclusion -- References -- 10 Cloud Cost Intelligence Using Machine Learning -- 1 Introduction -- 2 Literature Review -- 3 Materials and Methods -- 4 Results and Recommendations -- 5 Conclusion -- References -- 11 Mining Deeper Insights from Texts Using Unsupervised NLP -- 1 Introduction -- 2 Literature Review -- 3 Materials and Methods -- 4 Result -- 5 Conclusion -- References -- 12 Explainable AI for ML Ops -- 1 Introduction -- 1.1 ML and The "Last Mile" Problem -- 1.2 Keeping Tabs on the Model -- 1.3 Explainable AI for Model Monitoring -- 2 Literature Review -- 2.1 AI/ML Maturity -- 2.2 Rise of ML Ops -- 2.3 ML Ops in Postproduction -- 3 Materials and Methods -- 3.1 Datasets -- 3.2 Explainable AI 101 -- 3.3 Explainability and ML Monitoring -- 4 Exploratory Data Analysis -- 5 Experimental Analysis -- 6 Results -- 6.1 SOLUTION 1: Local Explanation with One Particular Observation -- 6.2 SOLUTION 2: Global Monitoring: Iterating the Model 100 Times, Introduce the Manipulation from the 30th Iteration -- 7 Conclusion -- References Business-Data processing Bhatavdekar, Mandar Sonstige oth Erscheint auch als Druck-Ausgabe Sharma, Neha World of Business with Data and Analytics Singapore : Springer,c2022 9789811956881 |
| spellingShingle | Sharma, Neha World of Business with Data and Analytics Intro -- Preface -- Acknowledgements -- Contents -- About the Editors -- 1 Dynamic Demand Planning for Distorted Historical Data Due to Pandemic -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 4 Results -- 5 Conclusion -- References -- 2 Cognitive Models to Predict Pipeline Leaks and Ruptures -- 1 Introduction -- 2 Literature Review -- 3 Material and Methodology -- 3.1 Defining the Solution Using Data and Analytics -- 4 Results -- 5 Conclusion -- References -- 3 Network Optimization of the Electricity Grid to Manage Distributed Energy Resources Using Data and Analytics -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Defining a Network Optimization Solution to Build an Agile Grid -- 3.2 Defining the Problem -- 3.3 Defining a Solution for the Problem -- 4 Results -- 5 Conclusion -- References -- 4 Enhancing Market Agility Through Accurate Price Indicators Using Contextualized Data Analytics -- 1 Introduction -- 2 Literature Review -- 3 Data-Flow in Utility Value Chain -- 4 Handaling Market data Volatility and Coherency -- 5 Leveraging Data Analytics in Improving Accuracy of Price-Prediction Models -- 6 Data-Reliant Congestion Management -- 7 Unlocking Techno Commercial Benefits to Utility -- 8 Conclusion -- References -- 5 Infrastructure for Automated Surface Damage Classification and Detection in Production Industries Using ResUNet-based Deep Learning Architecture -- 1 Introduction -- 2 Literature Review -- 3 Dataset Description -- 4 Methodology -- 4.1 Two-Phase Learning Approach -- 5 Results -- 6 Conclusion -- References -- 6 Cardiac Arrhythmias Classification and Detection for Medical Industry Using Wavelet Transformation and Probabilistic Neural Network Architecture -- 1 Introduction -- 2 Literature Review -- 3 The Solution -- 3.1 Discrete Wavelet Transformation -- 3.2 Probabilistic Neural Network 4 Experimental Outcome -- 5 Results and Discussion -- 6 Conclusion -- References -- 7 Investor Behavior Towards Mutual Fund -- 1 Introduction -- 2 Literature Review -- 3 Materials and Methods -- 4 Experimental Result and Evaluation -- 5 Results and Discussions -- 6 Conclusion and Future Scope -- References -- 8 iMask-An Artificial Intelligence Based Redaction Engine -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 4 Results -- 5 Conclusion -- References -- 9 Intrusion Detection System Using Signature-Based Detection and Data Mining Technique -- 1 Introduction -- 2 Literature Review -- 3 Materials and Methods -- 4 Experimental Result and Evaluation -- 5 Conclusion -- References -- 10 Cloud Cost Intelligence Using Machine Learning -- 1 Introduction -- 2 Literature Review -- 3 Materials and Methods -- 4 Results and Recommendations -- 5 Conclusion -- References -- 11 Mining Deeper Insights from Texts Using Unsupervised NLP -- 1 Introduction -- 2 Literature Review -- 3 Materials and Methods -- 4 Result -- 5 Conclusion -- References -- 12 Explainable AI for ML Ops -- 1 Introduction -- 1.1 ML and The "Last Mile" Problem -- 1.2 Keeping Tabs on the Model -- 1.3 Explainable AI for Model Monitoring -- 2 Literature Review -- 2.1 AI/ML Maturity -- 2.2 Rise of ML Ops -- 2.3 ML Ops in Postproduction -- 3 Materials and Methods -- 3.1 Datasets -- 3.2 Explainable AI 101 -- 3.3 Explainability and ML Monitoring -- 4 Exploratory Data Analysis -- 5 Experimental Analysis -- 6 Results -- 6.1 SOLUTION 1: Local Explanation with One Particular Observation -- 6.2 SOLUTION 2: Global Monitoring: Iterating the Model 100 Times, Introduce the Manipulation from the 30th Iteration -- 7 Conclusion -- References Business-Data processing |
| title | World of Business with Data and Analytics |
| title_auth | World of Business with Data and Analytics |
| title_exact_search | World of Business with Data and Analytics |
| title_exact_search_txtP | World of Business with Data and Analytics |
| title_full | World of Business with Data and Analytics |
| title_fullStr | World of Business with Data and Analytics |
| title_full_unstemmed | World of Business with Data and Analytics |
| title_short | World of Business with Data and Analytics |
| title_sort | world of business with data and analytics |
| topic | Business-Data processing |
| topic_facet | Business-Data processing |
| work_keys_str_mv | AT sharmaneha worldofbusinesswithdataandanalytics AT bhatavdekarmandar worldofbusinesswithdataandanalytics |