Fundamentals of Machine Learning for Corporate Finance

This book offers a clear and rigorous introduction to the use of machine learning in corporate finance. It explains how companies have moved from budgets, ratios, and spreadsheets to predictive models capable of forecasting sales, estimating liquidity, classifying risks, detecting fraud, and supporting strategic decisions. Without requiring advanced programming knowledge, the book combines financial theory, data science, AI ethics, case studies, and reproducible code in Python and R. Its approach is academic, yet accessible: designed for college students, entrepreneurs, financial analysts, and young professionals who want to understand the digital transformation of finance without losing sight of human judgment. The central message is straightforward: algorithms do not replace financial judgment; they expand upon it, challenge it, and compel us to document it more thoroughly.