Predictive Analytics

di Chuck Sherman (Autore)

Chuck Sherman, 2025

"Predictive Analytics: Unlocking the Power of Data for Business Success" is a comprehensive guide to using data analysis and prediction to drive business success. Written by a team of experts in the field, the book covers everything from the fundamentals of data analysis and statistical inference to the latest techniques in predictive analytics. The authors provide practical examples of how predictive analytics can be used in a variety of applications, including customer churn prediction, fraud detection, recommender systems, sales forecasting, healthcare analytics, and supply chain optimization. They explore a range of techniques, including linear regression, logistic regression, decision trees, random forests, gradient boosting, neural networks, and deep learning. The book also covers time series forecasting and text analytics, with detailed explanations of ARIMA models, seasonal decomposition, exponential smoothing, text preprocessing, text classification, sentiment analysis, topic modeling, and named entity recognition. The authors discuss ethical considerations in predictive analytics, including bias and fairness, privacy and security, transparency and accountability, and regulation and compliance. They also look to the future of predictive analytics, discussing advances in AI and machine learning, new techniques for big data analysis, the impact of quantum computing, and the rise of augmented analytics. With its accessible writing style and detailed examples, "Predictive Analytics: Unlocking the Power of Data for Business Success" is an essential resource for anyone interested in using data to gain a competitive advantage in their industry. Whether you are a student, a researcher, or a business professional, this book will provide you with the tools and knowledge you need to succeed in the world of predictive analytics.

• Autore: Chuck Sherman
• Durata in (hh:mm:ss): 03:31:47
• Anno edizione: 2025
• Editore: Chuck Sherman
• Lingua: Inglese
• EAN: 9798347816668