Artificial intelligence and machine learning for business : a no-nonsense guide to data driven technologies / Steven Finlay.

Includes bibliographical references (pages 174-182).

What are machine learning and artificial intelligence (AI)? -- What do the scores generated by a predictive model represent? -- Why use machine learning? What value does it add? -- How does machine learning work? -- Using a predictive model to make decisions -- That's scorecards, but what about decision trees? -- Neural networks and deep learning -- Unsupervised and reinforcement learning -- How to build a predictive model -- Operationalizing machine learning -- The relationship between big data and machine learning -- Ethics, law, and the GDPR -- The cutting edge of machine learning -- When can I buy a self-driving car? -- Concluding remarks -- Appendices: Evaluating predictive models ; Further information and recommended reading ; Popular terms in machine learning and AI ; A checklist for business success.

"Artificial Intelligence (AI) and Machine Learning are now mainstream business tools. They are being applied across many industries to increase profits, reduce costs, save lives and improve customer experiences. Consequently, organizations which understand these tools and know how to use them are benefiting at the expense of their rivals. Artificial Intelligence and Machine Learning for Business cuts through the hype and technical jargon that is often associated with these subjects. It delivers a simple and concise introduction for managers and business people. The focus is very much on practical application and how to work with technical specialists (data scientists) to maximize the benefits of these technologies"--Back cover.