Alfred Essa – författare

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 learning

How to apply the core technical concepts to solve business problems

The different methods used to evaluate AI models

How to understand model development as a tradeoff between accuracy and generalization

How to represent the computational aspects of AI using vectors and matrices

How to express the models in Python by using machine learning libraries such as scikit-learn, statsmodels, and keras　

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 learning

How to apply the core technical concepts to solve business problems

The different methods used to evaluate AI models

How to understand model development as a tradeoff between accuracy and generalization

How to represent the computational aspects of AI using vectors and matrices

How to express the models in Python by using machine learning libraries such as scikit-learn, statsmodels, and keras　

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 learning How to apply the core technical concepts to solve business problems The different methods used to evaluate AI models How to understand model development as a tradeoff between accuracy and generalization How to represent the computational aspects of AI using vectors and matrices How to express the models in Python by using machine learning libraries such as scikit-learn, statsmodels, and keras

Artificial Intelligence: Shaping the Future of Innovation provides a concise non-technical introduction to artificial intelligence as the key driver of innovation in the new economy. The book positions AI as a General Purpose Technology, vital for driving advancements across all sectors of business, government, and society.Written for leaders, innovators, and decision-makers, this book bridges the gap between technical complexity and practical application, demystifying AI's core concepts while illuminating its catalytic impact across industries and organizations. Through a careful examination of innovation dynamics, computational foundations, and core AI principles, readers will gain the essential knowledge needed to both understand and effectively navigate the AI landscape.This succinct guide makes technical concepts accessible—from algorithms and machine learning to deep learning and generative AI—giving leaders the clarity they need to engage confidently with AI technology.

Artificial Intelligence: Shaping the Future of Innovation provides a concise non-technical introduction to artificial intelligence as the key driver of innovation in the new economy. The book positions AI as a General Purpose Technology, vital for driving advancements across all sectors of business, government, and society.Written for leaders, innovators, and decision-makers, this book bridges the gap between technical complexity and practical application, demystifying AI's core concepts while illuminating its catalytic impact across industries and organizations. Through a careful examination of innovation dynamics, computational foundations, and core AI principles, readers will gain the essential knowledge needed to both understand and effectively navigate the AI landscape.This succinct guide makes technical concepts accessible-from algorithms and machine learning to deep learning and generative AI-giving leaders the clarity they need to engage confidently with AI technology.

This book demonstrates teachers’ and learners’ experiences with big data in education; education and cloud computing; and new technologies for teacher support. It also discusses the advantages of using these frontier technologies in teaching and learning and predicts the future challenges. As such, it enables readers to better understand how technologies can improve learning and teaching experiences. It is intended for graduates and scholars in educational technology disciplines and anyone interested in the applications of frontier technologies in education.

This book demonstrates teachers’ and learners’ experiences with big data in education; education and cloud computing; and new technologies for teacher support. It also discusses the advantages of using these frontier technologies in teaching and learning and predicts the future challenges. As such, it enables readers to better understand how technologies can improve learning and teaching experiences. It is intended for graduates and scholars in educational technology disciplines and anyone interested in the applications of frontier technologies in education.