{"product_id":"9789819247981","title":"Fundamentals for Data Science, Vol. II Machine Learning, High-Dimensional Inference, and Modern Data Applications","description":"\u003ch1\u003eFundamentals for Data Science, Vol. II\u003c\/h1\u003e\u003ch2\u003eMachine Learning, High-Dimensional Inference, and Modern Data Applications\u003c\/h2\u003e\u003ch3\u003eBhargab Chattopadhyay | Gaurangadeb Chattopadhyay | Tapabrata Maiti | Prasenjit Majumder\u003c\/h3\u003e\u003cdiv\u003e\u003cb\u003eComputers \/ Database Administration \u0026amp; Management\u003c\/b\u003e\u003c\/div\u003e\u003cbr\u003e\u003cdiv\u003e\n\u003cp class=\"MsoNormal\"\u003eThis volume builds upon the statistical and computational foundations established in Volume 1, advancing readers into modern machine learning, high-dimensional inference, and specialized data analysis domains. This volume focuses on scalable modeling techniques, algorithmic learning, and contemporary applications that define today’s data science practice.\u003c\/p\u003e\r\n\u003cp class=\"MsoNormal\"\u003eBeginning with classification methods and model selection techniques, the volume systematically introduces tree-based algorithms, ensemble learning, and penalized regression approaches for high-dimensional data. Both supervised and unsupervised learning paradigms are covered, including clustering, factor analysis, survival analysis, and image data analysis, providing breadth across methodological domains.\u003c\/p\u003e\r\n\u003cp class=\"MsoNormal\"\u003eA distinguishing feature of this volume is its integration of statistical principles with modern machine learning, offering readers a unified perspective on inference, regularization, generalization, and interpretability. Advanced chapters explore text analytics, deep learning from a statistical viewpoint, spatial data analysis, and portfolio risk modeling, highlighting real-world relevance across finance, public policy, and urban analytics.\u003c\/p\u003e\r\n\u003cp class=\"MsoNormal\"\u003eThroughout the volume, theory is reinforced with practical implementations, case studies, and data-driven illustrations, enabling readers to transition from classical analytics to advanced data science workflows. This volume is intended for students, researchers, and practitioners who have mastered foundational concepts and seek to apply cutting-edge analytical techniques in complex, real-world settings.\u003c\/p\u003e\n\u003c\/div\u003e\u003cdiv\u003e\n\u003cp class=\"MsoNormal\"\u003e\u003cstrong\u003eBhargab Chattopadhyay\u003c\/strong\u003e is Associate Professor at the School of Management \u0026amp; Entrepreneurship, Indian Institute of Technology Jodhpur in the DTBI\/Operations area. His research interests lie in the area of core set construction, sequential analysis, and inference. He has worked on several projects and is serving as the Associate Editor of the journal \u003cem\u003eSequential Analysis\u003c\/em\u003e.\u003c\/p\u003e\r\n\u003cp class=\"MsoNormal\"\u003e\u003cstrong\u003eGaurangadeb Chattopadhyay\u003c\/strong\u003e is Professor in the Department of Statistics at the University of Calcutta, India. He has several publications in journals like Statistics in Medicine, \u003cem\u003eScandinavian Journal of Statistics\u003c\/em\u003e, \u003cem\u003eStatistical Papers\u003c\/em\u003e, and others.\u003c\/p\u003e\r\n\u003cp class=\"MsoNormal\"\u003e\u003cstrong\u003eTapabrata Maiti\u003c\/strong\u003e is Professor and Graduate Director in the Department of Statistics \u0026amp; Probability at Michigan State University, USA. He has secondary appointment with the Department of Marketing, Eli Broad School of Business, and is co-director in the Center for Business and Social Analytics. He has several publications in journals like \u003cem\u003eAnnals of Statistics\u003c\/em\u003e, \u003cem\u003eJournal of Royal Statistical Society Series B\u003c\/em\u003e, \u003cem\u003eJournal of the American Statistical Association\u003c\/em\u003e to name some, and is working on several projects funded by federal USA agencies like National Science Foundation (NSF) and National Institutes of Health (NIH).\u003c\/p\u003e\r\n\u003cp class=\"MsoNormal\"\u003e\u003cstrong\u003ePrasenjit Majumder\u003c\/strong\u003e is Visiting Faculty at The Chatterjee Group's Centres for Research and Education in Science and Technology (TCG CREST), Kolkata, India; and Professor at Dhirubhai Ambani University, Gandhinagar, India. He has worked on several projects funded by different government agencies. He has authored a monograph and edited two volumes.\u003c\/p\u003e\n\u003c\/div\u003e\u003cbr\u003e\u003ctable\u003e\n\u003ctr\u003e\n\u003ctd\u003ePublication Date: \u003c\/td\u003e\n\u003ctd\u003e17 January 2027\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003ePublisher: \u003c\/td\u003e\n\u003ctd\u003eSpringer Nature Singapore\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eImprint: \u003c\/td\u003e\n\u003ctd\u003eSpringer\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eISBN-13: \u003c\/td\u003e\n\u003ctd\u003e9789819247981\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eFormat: \u003c\/td\u003e\n\u003ctd\u003eMultiple component retail product part s\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/table\u003e","brand":"Springer Nature Singapore","offers":[{"title":"Default Title","offer_id":51460151410828,"sku":"9789819247981","price":125.99,"currency_code":"USD","in_stock":true}],"url":"https:\/\/lateknightbooks.com\/products\/9789819247981","provider":"Late Knight Books and Services, LLC","version":"1.0","type":"link"}