Description

Book Synopsis
Most economists agree that AI is a general purpose technology (GPT) like the steam engine, electricity, and the computer. AI will drive innovation in all sectors of the economy for the foreseeable future. Practical AI for Business Leaders, Product Managers, and Entrepreneurs is a technical guidebook for the business leader or anyone responsible for leading AI-related initiatives in their organization. The book can also be used as a foundation to explore the ethical implications of AI. Authors Alfred Essa and Shirin Mojarad provide a gentle introduction to foundational topics in AI. Each topic is framed as a triad: concept, theory, and practice. The concept chapters develop the intuition, culminating in a practical case study. The theory chapters reveal the underlying technical machinery. The practice chapters provide code in Python to implement the models discussed in the case study. With this book, readers will learn: The technical foundations of machine learning and deep lea

Table of Contents

Introduction

What is AI and why it is at the center of major business transformation?

How is it related to machine learning?

What is deep learning, and how is it related to ML?

Why is it important?

How the book is organized

Who is the audience?


Section 1: Machine Learning Chapter 1.1, introduction, machine learning, different types of machine learning 

Chapter 1.2, Machine Learning Technical Overview 

Chapter 1.3, Hands-On Machine Learning with Scikit Learn

Chapter 1.4,  Advanced Topics/flavors of Machine learning

Appendix: mathematical interlude


Section 2: Deep Learning 

Chapter 2.1, introduction (what is it, why is it important)

Chapter 2.2, Deep Learning Technical Overview 

Chapter 2.3, Hands-On Deep Learning with Keras

Chapter 2.4,  Advanced Topics/flavors of deep learning

Appendix: mathematical interlude


Section 3: Putting AI into Practice: Innovation Framework

Chapter 3.1: Diffusion and Dynamics of Innovation

Chapter 3.2: Managing an Innovation Portfolio

Practical AI for Business Leaders Product

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    Order before 4pm today for delivery by Thu 18 Jun 2026.

    A Paperback / softback by Alfred Essa, Shirin Mojarad

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      Publisher: De Gruyter
      Publication Date: 04/04/2022
      ISBN13: 9781501514647, 978-1501514647
      ISBN10: 1501514644

      Description

      Book Synopsis
      Most economists agree that AI is a general purpose technology (GPT) like the steam engine, electricity, and the computer. AI will drive innovation in all sectors of the economy for the foreseeable future. Practical AI for Business Leaders, Product Managers, and Entrepreneurs is a technical guidebook for the business leader or anyone responsible for leading AI-related initiatives in their organization. The book can also be used as a foundation to explore the ethical implications of AI. Authors Alfred Essa and Shirin Mojarad provide a gentle introduction to foundational topics in AI. Each topic is framed as a triad: concept, theory, and practice. The concept chapters develop the intuition, culminating in a practical case study. The theory chapters reveal the underlying technical machinery. The practice chapters provide code in Python to implement the models discussed in the case study. With this book, readers will learn: The technical foundations of machine learning and deep lea

      Table of Contents

      Introduction

      What is AI and why it is at the center of major business transformation?

      How is it related to machine learning?

      What is deep learning, and how is it related to ML?

      Why is it important?

      How the book is organized

      Who is the audience?


      Section 1: Machine Learning Chapter 1.1, introduction, machine learning, different types of machine learning 

      Chapter 1.2, Machine Learning Technical Overview 

      Chapter 1.3, Hands-On Machine Learning with Scikit Learn

      Chapter 1.4,  Advanced Topics/flavors of Machine learning

      Appendix: mathematical interlude


      Section 2: Deep Learning 

      Chapter 2.1, introduction (what is it, why is it important)

      Chapter 2.2, Deep Learning Technical Overview 

      Chapter 2.3, Hands-On Deep Learning with Keras

      Chapter 2.4,  Advanced Topics/flavors of deep learning

      Appendix: mathematical interlude


      Section 3: Putting AI into Practice: Innovation Framework

      Chapter 3.1: Diffusion and Dynamics of Innovation

      Chapter 3.2: Managing an Innovation Portfolio

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