Text analytics with Python

The Weygandt approach builds student mastery of managerial accounting concepts.The Weygandt approach presents students with a dynamic and thorough overview of managerial accounting topics, building concept mastery and helping students understand the value of accounting to the real world. A clear and relevant exposition, engaging visuals and supporting examples, and valuable end-of-chapter material, work together to build students' confidence and mastery of accounting concepts and skills.Bulleted text and numbered approach keep students engaged in core concepts.New to the International edition, the bulleted text and numbered approach eliminates long, intimidating paragraphs and highlights important concepts as students read through the content. This approach breaks down the most important information students need to know, improving their study experience, and keeping them engaged and on track during the course.Data analytics focus builds students' data literacy and decision-making skil

With the advent of the Al era, professionals need to select the right tools to meet new opportunities and challenges! This instructional material focuses on the application of big data analysis, text mining, and machine learning in auditing to assist readers in understanding the latest developments in data analysis and smart audit.JCAATs is a new generation audit software developed by Python, which can be executed in a Windows and MAC operation systems with a multi-language, visual, and easy-to-use interface. Non-IT professionals can easily conduct smart data analysis. Through JCAATs' built-in data fusion technology and OPEN DATA connector, heterogeneous data can be quickly analyzed in real-time and effectively identifying anomalies. The features of this book include:The book is structured to provide a progressive learning experience, with chapters covering different concepts and applications, as well as exercises and practice questions. The official textbook endorsed by ICAEA

Business Research Methods, 14e, contains stand-alone chapters that reflect research industry practices using real examples from all areas of business. In collaborations with over two dozen industry researchers, Schindler writes a real-world research methods book that distinguishes between big data analytics and small data with an emphasis on decision making. She eloquently covers ethical issues and their solutions, and has added more coverage of process models, sampling how-to, and data preparation.Conscious of the different learning styles of students, Schindler provides appropriate cues for both visual and verbal learners through the use of in-text exhibits, bolded key terms, conceptual photos throughout and research though-leader quotes in PowerPoints for each chapter. She also used various interim GreenBook Research Industry Trends (GRIT) reports to guide the research for this revision. The latest GRIT Report is based on the largest study of research suppliers and users ever conduc