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Book synopsis

Reactive Publishing

Turn spreadsheets into intelligent prediction engines.
In Machine Learning for Excel, finance author Hayden Van Der Post reveals how to transform the world's most familiar tool into a powerful platform for data-driven forecasting and decision-making.

Built for analysts, finance professionals, and business leaders, this guide bridges the gap between Excel simplicity and machine learning sophistication, no coding required. Learn how to automate complex forecasting models, design self-optimizing dashboards, and unlock hidden financial insights that drive competitive advantage.

Through step-by-step applications and real-world case studies, you'll discover how to:

• Integrate Excel with Python and AI tools to automate repetitive modeling tasks.

• Build predictive analytics systems directly within Excel.

• Design data pipelines and forecasting frameworks that learn and adapt over time.

• Turn your organization's spreadsheets into strategic, self-improving assets.

• Apply machine intelligence to corporate finance, FP&A, and strategic planning.

Whether you're an FP&A analyst, data-driven CFO, or entrepreneur, Machine Learning for Excel empowers you to move beyond formulas, into a new era of intelligent automation and insight.

Who This Book Is For

Professionals in finance, operations, or data analytics who want to harness AI without leaving Excel. Ideal for CFOs, financial analysts, controllers, data scientists, and anyone building a competitive edge through smarter automation.

Book details

• Full title: Machine Learning for Excel
• Subtitle: Automate Forecasting, Build Predictive Models, and Unlock Financial Insights: A Practical Guide to Building Intelligent Financial Models Without Leaving Excel
• Author: Hayden Van Der Post, Alice Schwartz
• Language: English
• Binding: Paperback
• Number of pages: 708
• EAN: 9798271896385
• ID: 50583365
• Publisher: Independently published
• Weight: 1208 g
• Dimensions: 254 × 178 × 36 mm
• Date of publishing: 28. October 2025

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