World of business with data and analytics / / edited by Neha Sharma, Mandar Bhatavdekar

• Pubblicazione: Singapore : , : Springer, , [2022]; ©2022
• Descrizione fisica: 1 online resource (211 pages)
• Disciplina: 260
• Soggetto topico: Business - Data processing
• Persona (resp. second.): SharmaNeha; BhatavdekarMandar
• Nota di bibliografia: Includes bibliographical references.
• Nota di contenuto: 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.
• Titolo autorizzato: World of business with data and analytics
• ISBN: 981-19-5689-8
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 996490358303316
• Lo trovi qui: Univ. di Salerno
• Serie: Studies in Autonomic, Data-Driven and Industrial Computing