Practical AI for Business Leaders, Product Managers, and Entrepreneurs by Alfred Essa

£45.50
Available
Product Ref. (e.g. ISBN, SKU)
9781501514647
Published:
04 Apr 2022
Format:
Paperback
Number of pages:
260 pages
Dimensions:
240x170x22mm
Weight:
0.402kgs
Author:
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.

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 

About the Author: Alfred Essa has led advanced analytics, machine learning, and information technology teams in academia and industry. He has served as Simon Fellow at Carnegie Mellon University, VP of Analytics and R&D at McGraw Hill Education, and CIO at MIT's Sloan School of Management. He is a graduate of Haverford College and Yale University. Shirin Mojarad is a senior machine learning specialist at Google Cloud. Previously, she was a senior data scientist at Apple where she worked on AB experimentation, causal inference, and metrics design. She has experience applying AI and machine learning to five vertical markets in Big Data: healthcare, finance, educational technology, high tech, and cloud technology. She received her master's and Ph.D. from Newcastle University, United Kingdom.

More Information
Number of pages 260

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