LEADER 04201nam 22006255 450 001 9910616374303321 005 20251009105935.0 010 $a9789811956898 010 $a9811956898 024 7 $a10.1007/978-981-19-5689-8 035 $a(MiAaPQ)EBC7102107 035 $a(Au-PeEL)EBL7102107 035 $a(CKB)24950459600041 035 $a(PPN)264958438 035 $a(DE-He213)978-981-19-5689-8 035 $a(OCoLC)1346986780 035 $a(EXLCZ)9924950459600041 100 $a20220928d2022 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aWorld of Business with Data and Analytics /$fedited by Neha Sharma, Mandar Bhatavdekar 205 $a1st ed. 2022. 210 1$aSingapore :$cSpringer Nature Singapore :$cImprint: Springer,$d2022. 215 $a1 online resource (211 pages) 225 1 $aStudies in Autonomic, Data-driven and Industrial Computing,$x2730-6445 311 08$aPrint version: Sharma, Neha World of Business with Data and Analytics Singapore : Springer,c2022 9789811956881 320 $aIncludes bibliographical references. 327 $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. . 330 $aThis book covers research work spanning the breadth of ventures, a variety of challenges and the finest of techniques used to address data and analytics, by subject matter experts from the business world. The content of this book highlights the real-life business problems that are relevant to any industry and technology environment. This book helps us become a contributor to and accelerator of artificial intelligence, data science and analytics, deploy a structured life-cycle approach to data related issues, apply appropriate analytical tools & techniques to analyze data and deliver solutions with a difference. It also brings out the story-telling element in a compelling fashion using data and analytics. This prepares the readers to drive quantitative and qualitative outcomes and apply this mindset to various business actions in different domains such as energy, manufacturing, health care, BFSI, security, etc. 410 0$aStudies in Autonomic, Data-driven and Industrial Computing,$x2730-6445 606 $aComputational intelligence 606 $aArtificial intelligence 606 $aQuantitative research 606 $aComputational Intelligence 606 $aArtificial Intelligence 606 $aData Analysis and Big Data 615 0$aComputational intelligence. 615 0$aArtificial intelligence. 615 0$aQuantitative research. 615 14$aComputational Intelligence. 615 24$aArtificial Intelligence. 615 24$aData Analysis and Big Data. 676 $a260 702 $aSharma$b Neha 702 $aBhatavdekar$b Mandar 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910616374303321 996 $aWorld of business with data and analytics$93020079 997 $aUNINA