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001450053 003__ OCoLC
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001450053 019__ $$a1346535435
001450053 020__ $$a9789811956898$$q(electronic bk.)
001450053 020__ $$a9811956898$$q(electronic bk.)
001450053 020__ $$z9789811956881
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001450053 0247_ $$a10.1007/978-981-19-5689-8$$2doi
001450053 035__ $$aSP(OCoLC)1346986780
001450053 040__ $$aGW5XE$$beng$$erda$$epn$$cGW5XE$$dEBLCP$$dYDX$$dOCLCF$$dOCLCQ
001450053 049__ $$aISEA
001450053 050_4 $$aQA76.9.D343
001450053 08204 $$a006.3/12$$223/eng/20221007
001450053 24500 $$aWorld of business with data and analytics /$$cNeha Sharma, Mandar Bhatavdekar, editors.
001450053 264_1 $$aSingapore :$$bSpringer,$$c2022.
001450053 300__ $$a1 online resource (xiv, 201 pages) :$$billustrations (some color).
001450053 336__ $$atext$$btxt$$2rdacontent
001450053 337__ $$acomputer$$bc$$2rdamedia
001450053 338__ $$aonline resource$$bcr$$2rdacarrier
001450053 4901_ $$aStudies in autonomic, data-driven and industrial computing,$$x2730-6445
001450053 5050_ $$aChapter 1. Dynamic Demand Planning for Distorted Historical Data Due to Pandemic -- Chapter 2. Cognitive Models to Predict Pipeline Leaks and Ruptures -- Chapter 3. Network Optimization of the Electricity Grid to manage Distributed Energy Resources using Data & Analytics -- Chapter 4. Enhancing Market Agility Through Accurate Price Indicators using Contextualized Data Analytics -- Chapter 5. Infrastructure for Automated Surface Damage Classification and Detection in Production industries using ResUNet based Deep Learning Architecture -- Chapter 6. Cardiac Arrhythmias Classification & Detection for Medical Industry Using Wavelet Transformation & Probabilistic Neural Network Architecture -- Chapter 7. Investor Behavior towards Mutual Fund -- Chapter 8. iMask : An Artificial Intelligence Based Redaction Engine -- Chapter 9. Artificial Intelligence for Proactive Vulnerability Prediction and interpretability using Occlusion -- Chapter 10. Intrusion Detection System using Signature based Detection and Data Mining Technique. Chapter 11. Cloud Cost Intelligence using Machine Learning -- Chapter 12. Mining deeper Insights using Unsupervised NLP -- Chapter 13. Explainable AI for ML OPS.
001450053 506__ $$aAccess limited to authorized users.
001450053 520__ $$aThis book covers research work spanning the breadth of ventures, a variety of challenges and the finest of techniques used to address data and analytics, by subject matter experts from the business world. The content of this book highlights the real-life business problems that are relevant to any industry and technology environment. This book helps us become a contributor to and accelerator of artificial intelligence, data science and analytics, deploy a structured life-cycle approach to data related issues, apply appropriate analytical tools & techniques to analyze data and deliver solutions with a difference. It also brings out the story-telling element in a compelling fashion using data and analytics. This prepares the readers to drive quantitative and qualitative outcomes and apply this mindset to various business actions in different domains such as energy, manufacturing, health care, BFSI, security, etc.
001450053 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed October 7, 2022).
001450053 650_0 $$aData mining.
001450053 650_0 $$aBusiness$$xData processing.
001450053 655_0 $$aElectronic books.
001450053 7001_ $$aSharma, Neha,$$eeditor.
001450053 7001_ $$aBhatavdekar, Mandar,$$eeditor.
001450053 77608 $$iPrint version: $$z981195688X$$z9789811956881$$w(OCoLC)1335114310
001450053 830_0 $$aStudies in autonomic, data-driven and industrial computing,$$x2730-6445
001450053 852__ $$bebk
001450053 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-981-19-5689-8$$zOnline Access$$91397441.1
001450053 909CO $$ooai:library.usi.edu:1450053$$pGLOBAL_SET
001450053 980__ $$aBIB
001450053 980__ $$aEBOOK
001450053 982__ $$aEbook
001450053 983__ $$aOnline
001450053 994__ $$a92$$bISE