Machine Learning for Managers

ISBN-13: 9781032362427 / Angielski

New Zealand) Geertsema Paul (University of Auckland

Opis

This book is for managers who have been afraid of machine learning but want to understand it. It helps managers understand how machine learning works, what it can do and how it can be used to create value in the context of wider organisation. It will appeal to managers who want to learn more about machine learning applications in business.

Machine learning can help managers make better predictions, automate complex tasks and improve business operations. Managers who are familiar with machine learning are better placed to navigate the increasingly digital world we live in. There is a view that machine learning is a highly technical subject that can only be understood by specialists. However, many of the ideas that underpin machine learning are straightforward and accessible to anyone with a bit of curiosity. This book is for managers who want to understand what machine learning is about, but who lack a technical background in computer science, statistics or math.

The book describes in plain language what machine learning is and how it works. In addition, it explains how to manage machine learning projects within an organization.

This book should appeal to anyone that wants to learn more about using machine learning to drive value in real-world organizations.

Spis treści

Part 1: Understanding Machine Learning  1. Let's jump right in  2. Different kinds of ML  3. Creating ML models  4. Linear models  5. Neural networks  6. Tree-based approaches, ensembles and boosting  7. Dimensionality reduction and clustering  8. Unstructured data  9. Explainable AI  Part 2: Managing Machine Learning Projects  10. The ML system lifecycle  11. The big picture  12. Creating value with ML  13. Making the business case  14. The ML pipeline  15. Development  16. Deployment and monitoring 

O autorze

Paul Geertsema is an academic and consultant in the areas of finance, data science and machine learning. His research involves the application of contemporary machine learning methods to solving problems in finance and business. He teaches Modern Investment Theory and Management (final-year undergraduate) and Financial Machine Learning (postgraduate) at the University of Auckland. Dr Geertsema has published in numerous international peer-reviewed journals, including the Journal of Accounting Research and the Journal of Banking and Finance, and serves on the board of the AI Researchers Association. Prior to his return to academia, Dr Geertsema worked at Barclays Capital as a derivatives trader in Hong Kong and as a sell-side research analyst in London.