04189nam a22004935i 4500001001800000003000900018005001700027007001500044008004100059020003700100024003500137050001200172072001700184072002300201072001600224100008200240245013600322250001800458264007900476300006600555336002600621337002600647338003600673347002400709505029600733520210901029650003403138650004703172650002903219650005903248650003403307650001903341650002903360650004603389710003403435773002603469776003603495776003603531776003603567856004603603912001403649912001503663999001703678978-3-031-54680-8DE-He21320251030112333.0cr nn 008mamaa240626s2024    sz |    s    |||| 0|eng d  a97830315468089978-3-031-54680-87 a10.1007/978-3-031-54680-82doi 4aHG176.7 7aKFFM2bicssc 7aBUS0270102bisacsh 7aKFFM2thema1 aKumar, Sunil.eauthor.4aut4http://id.loc.gov/vocabulary/relators/aut97392410aPython for Accounting and Financeh[electronic resource] :bAn Integrative Approach to Using Python for Research /cby Sunil Kumar.  a1st ed. 2024. 1aCham :bSpringer Nature Switzerland :bImprint: Palgrave Macmillan,c2024.  aXVI, 508 p. 500 illus., 33 illus. in color.bonline resource.  atextbtxt2rdacontent  acomputerbc2rdamedia  aonline resourcebcr2rdacarrier  atext filebPDF2rda0 aChapter 1: Introduction and Fundamentals -- Chapter 2: Data Acquisition and Cleaning -- Chapter 3: Exploratory Data Analysis and Visualization -- Chapter 4: Natural Language Processing and Text Analysis -- Chapter 5: Machine Learning and Predictive Analytics -- Chapter 6: Advanced Topics. .  aThis book is a comprehensive guide to the application of Python in accounting, finance, and other business disciplines. This book is more than a Python tutorial; it is an integrative approach to using Python for practical research in these fields. The book begins with an introduction to Python and its key libraries. It then covers real-world applications of Python, covering data acquisition, cleaning, exploratory data analysis, visualization, and advanced topics like natural language processing, machine learning, predictive analytics, and deep learning. What sets this book apart is its unique blend of theoretical knowledge and real-world examples, supplemented with ready-to-use code. It doesn't stop at the syntax; it shows how to apply Python to tackle actual analytical problems. The book uses case studies to illustrate how Python can enhance traditional research methods in accounting and finance, not only allowing the reader to gain a firm understanding of Python programming but also equipping them with the skills to apply Python to accounting, finance, and broader business research. Whether you are a PhD student, a professor, an industry professional, or a financial researcher, this book provides the key to unlocking the full potential of Python in research. Sunil Kumar, Ph.D., C.P.A., currently serves as an assistant professor of Accounting at the Mario J. Gabelli School of Business, Roger Williams University, USA. He is a seasoned academic with a diversified research portfolio. His innovative research approach is deeply rooted in the application of technology, distinguishing him in the academic field of accounting and finance. His command over Python and other advanced computational tools allows him to integrate complex technological processes into his research, enabling a nuanced and comprehensive understanding of accounting and finance phenomena. He is currently involved in several projects that use machine learning and deep learning approaches for predictive modeling in financial contexts, further emphasizing his commitment to leveraging technology in research. 0aFinancial engineering.958071 0aPython (Computer program language).964608 0aMachine learning.955059 0aNatural language processing (Computer science).96513114aFinancial Engineering.95807124aPython.94755324aMachine Learning.95505924aNatural Language Processing (NLP).9661642 aSpringerLink (Online service)0 tSpringer Nature eBook08iPrinted edition:z978303154679208iPrinted edition:z978303154681508iPrinted edition:z978303154682240uhttps://doi.org/10.1007/978-3-031-54680-8  aZDB-2-ECF  aZDB-2-SXEF  c61038d61038