Machine Learning and Deep Learning for Business Professionals: A Vibe-Modeling Approach – Paperback

Machine Learning and Deep Learning for Business Professionals: A Vibe-Modeling Approach introduces machine learning, deep learning, generative AI, and emerging agentic workflows through a distinctive “vibe-modeling” approach. Readers work iteratively with AI tools to explore concepts, generate and inspect Python code, test alternatives, and interpret results. This approach enables readers to engage with practical business applications without having to write Python programs from scratch, while emphasizing their responsibility to understand and evaluate the models they use.

The book develops two primary learning outcomes: an analytics mindset and model thinking. An analytics mindset helps readers frame business questions, assess the suitability and quality of data, and interpret evidence in context. Model thinking helps readers understand what models learn, evaluate their performance and limitations, assess the reliability of predicted probabilities, and judge how model outputs should inform business decisions.

Structured progressively, the book uses plain language, intuitive visualizations, and business applications to connect concepts with implementation. Beginning with AI and data foundations, it moves through Naive Bayes, regression, logistic regression, neural networks, decision trees, Random Forest, boosting, model evaluation, class imbalance, probability calibration, and threshold selection. Later chapters connect these foundations to large language models and agentic systems, showing how models fit into broader business workflows involving tools, project files, runtime controls, verification, and human oversight.

The book is designed for business students, instructors, and professionals, including managers, analysts, and accountants, who want to understand and use modern artificial intelligence without a background in computer science or advanced mathematics.