This thoroughly revised edition presents statistical concepts computationally, rather than mathematically, using programs written in Python. Through practical examples and exercises based on real-world datasets, you'll learn the entire process of exploratory data analysis-from wrangling data and generating statistics to identifying patterns.

Machine Learning for Business Analytics: Concepts, Techniques, and Applications in Python is a comprehensive introduction to and an overview of the methods that underlie modern AI. This best-selling textbook covers both statistical and machine learning (AI) algorithms for prediction, classification, visualization, dimension reduction, rule mining, recommendations, clustering, text mining, experimentation, network analytics and generative AI. Along with hands-on exercises and real-life case st...

Poole’s "Linear Algebra: A Modern Introduction, Cengage International Edition", 5th, emphasizes a vectors approach and prepares students to transition from computational to theoretical mathematics. Balancing theory and applications, the conversational writing style combines traditional presentation with student-centered learning. Theoretical, computational, and applied topics are presented in a flexible, integrated way. Stressing geometric understanding before computational techniques, vect...

Taalman and Kohn's refreshing new textbook is designed to help instructors do just that.Taalman and Kohn's Calculus offers a streamlined, structured exposition of calculus that combines the clarity of classic textbooks with a modern perspective on concepts, skills, applications, and theory.