BUILDING PREDICTIVE MODELS WITH REGRESSION ANALYSIS: How to use regression models to predict continuous variables based on data patterns

By Renata Sloane

Building Predictive Models with Regression Analysis is your ultimate guide to using regression techniques to predict continuous variables and uncover data patterns that drive business decisions. Whether you're a data science novice or an experienced analyst, this book provides a thorough understanding of regression models and how to implement them to create powerful predictive models. This book delves into the foundations of linear and multiple regression, helping you understand how to model relationships between variables and make accurate predictions. You'll also learn advanced regression techniques like polynomial regression, regularization, and time series forecasting. Through practical examples and hands-on projects, you'll gain expertise in selecting the right regression model, handling multicollinearity, evaluating model performance, and interpreting results for actionable insights. Learn how to use Python's powerful libraries such as Scikit-learn and statsmodels to build, validate, and fine-tune regression models. With clear explanations and real-world applications, you will be equipped to predict everything from sales figures and market trends to stock prices and customer behaviors. By the end of this book, you'll have the skills to develop robust predictive models that can help businesses forecast future outcomes based on past data patterns.

• Format: Paperback
• Language: English
• ISBN: B0F5NS27VG
• ISBN13: 9798280533592
• Release Date: April 2025
• Publisher: Independently published
• Length: 170 Pages
• Dimensions: 9.0" x 0.4" x 6.0"