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Neuro-Symbolic AI

Neuro-Symbolic AI

By : Alexiei Dingli, David Farrugia
3.7 (6)
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Neuro-Symbolic AI

Neuro-Symbolic AI

3.7 (6)
By: Alexiei Dingli, David Farrugia

Overview of this book

Neuro-symbolic AI offers the potential to create intelligent systems that possess both the reasoning capabilities of symbolic AI along with the learning capabilities of neural networks. This book provides an overview of AI and its inner mechanics, covering both symbolic and neural network approaches. You’ll begin by exploring the decline of symbolic AI and the recent neural network revolution, as well as their limitations. The book then delves into the importance of building trustworthy and transparent AI solutions using explainable AI techniques. As you advance, you’ll explore the emerging field of neuro-symbolic AI, which combines symbolic AI and modern neural networks to improve performance and transparency. You’ll also learn how to get started with neuro-symbolic AI using Python with the help of practical examples. In addition, the book covers the most promising technologies in the field, providing insights into the future of AI. Upon completing this book, you will acquire a profound comprehension of neuro-symbolic AI and its practical implications. Additionally, you will cultivate the essential abilities to conceptualize, design, and execute neuro-symbolic AI solutions.
Table of Contents (12 chapters)
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Application 3 – finance – bank loan risk assessment

In the ever-evolving world of finance, there is a growing need to stay ahead of the curve and be competitive. AI has proven to be a powerful tool in achieving this, providing financial institutions with real-time data processing, generating accurate predictions, and automating mundane and repetitive tasks. AI is not restricted to large financial organizations. Small and medium-sized companies can also exploit AI to provide valuable insights into operations and customer behavior. As regulations become increasingly complex and the threat of fraud looms, AI can also assist financial institutions in complying with regulations and detecting fraudulent activities. As the finance industry continues to evolve and adapt to the digital age, the importance and necessity of AI will only continue to grow.

Application details

Hatzilygeroudis, I. and Prentzas, J. (2011). Fuzzy and Neuro-Symbolic Approaches to Assessment of Bank...

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