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001			394079
003			ES-MaUEC
005			20230102123051.0
007			cr nn 008mamaa
008			220928s2022 si | s |||| 0|eng d
020			_a9789811956898
024	7		_a10.1007/978-981-19-5689-8 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC
245	1	0	_aWorld of Business with Data and Analytics _cedited by Neha Sharma, Mandar Bhatavdekar
250			_a1st edition 2022
264		1	_aSingapore _bSpringer International Publishing _c2022
300			_a1 recurso en línea (XVI, 201 páginas) _b141 ilustraciones, 114 ilustraciones a color
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF
490	0		_aStudies in Autonomic Data-driven and Industrial Computing _x2730-6445
505	0		_aChapter 1. Dynamic Demand Planning for Distorted Historical Data Due to Pandemic -- Chapter 2. Cognitive Models to Predict Pipeline Leaks and Ruptures -- Chapter 3. Network Optimization of the Electricity Grid to manage Distributed Energy Resources using Data & Analytics -- Chapter 4. Enhancing Market Agility Through Accurate Price Indicators using Contextualized Data Analytics -- Chapter 5. Infrastructure for Automated Surface Damage Classification and Detection in Production industries using ResUNet based Deep Learning Architecture -- Chapter 6. Cardiac Arrhythmias Classification & Detection for Medical Industry Using Wavelet Transformation & Probabilistic Neural Network Architecture -- Chapter 7. Investor Behavior towards Mutual Fund -- Chapter 8. iMask - An Artificial Intelligence Based Redaction Engine -- Chapter 9. Artificial Intelligence for Proactive Vulnerability Prediction and interpretability using Occlusion -- Chapter 10. Intrusion Detection System using Signature based Detection and Data Mining Technique. Chapter 11. Cloud Cost Intelligence using Machine Learning -- Chapter 12. Mining deeper Insights using Unsupervised NLP -- Chapter 13. Explainable AI for ML OPS. .
520			_aThis book covers research work spanning the breadth of ventures, a variety of challenges and the finest of techniques used to address data and analytics, by subject matter experts from the business world. The content of this book highlights the real-life business problems that are relevant to any industry and technology environment. This book helps us become a contributor to and accelerator of artificial intelligence, data science and analytics, deploy a structured life-cycle approach to data related issues, apply appropriate analytical tools & techniques to analyze data and deliver solutions with a difference. It also brings out the story-telling element in a compelling fashion using data and analytics. This prepares the readers to drive quantitative and qualitative outcomes and apply this mindset to various business actions in different domains such as energy, manufacturing, health care, BFSI, security, etc.
700	1		_aSharma, Neha _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt
700	1		_aBhatavdekar, Mandar _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt
776	0	8	_iPrinted edition: _z9789811956881
776	0	8	_iPrinted edition: _z9789811956904
776	0	8	_iPrinted edition: _z9789811956911
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-981-19-5689-8 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
988			_aSpringer_Computer_2022
999			_c394079 _d394079