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Neuro-Symbolic-AI

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Neuro-Symbolic AI, published by Packt

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# Neuro-Symbolic AI

This is the code repository for [Neuro-Symbolic AI](https://www.amazon.com/dp/1804617628), published by Packt.

**Design transparent and trustworthy systems that understand the world as you do**

## What is this book about?
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.

This book covers the following exciting features: 
* Gain an understanding of the intuition behind neuro-symbolic AI
* Determine the correct uses that can benefit from neuro-symbolic AI
* Differentiate between types of explainable AI techniques
* Think about, design, and implement neuro-symbolic AI solutions
* Create and fine-tune your first neuro-symbolic AI system
* Explore the advantages of fusing symbolic AI with modern neural networks in neuro-symbolic AI systems

If you feel this book is for you, get your [copy](https://www.amazon.com/dp/1804617628) today!

## Instructions and Navigations
All of the code is organized into folders.

The code will look like the following:
```
html, body, #map {
    height: 100%;
    margin: 0;
    padding: 0
}
```

**Following is what you need for this book:**
This book is ideal for data scientists, machine learning engineers, and AI enthusiasts who want to explore the emerging field of neuro-symbolic AI and discover how to build transparent and trustworthy AI solutions. A basic understanding of AI concepts and familiarity with Python programming are needed to make the most of this book.

With the following software and hardware list you can run all code files present in the book (Chapter 1-9).

### Software and Hardware List

| Chapter  | Software required                                                                    | OS required                        |
| -------- | -------------------------------------------------------------------------------------| -----------------------------------|
|  1-9		 |   		Python 3.7+ 					                                            			  | Windows, Mac OS X, and Linux (Any) |

We also provide a PDF file that has color images of the screenshots/diagrams used in this book. [Click here to download it](https://packt.link/94cl7).

### Related products <Other books you may enjoy>
* Hands-On Graph Neural Networks Using Python [[Packt]](https://www.packtpub.com/product/hands-on-graph-neural-networks-using-python/9781804617526) [[Amazon]](https://www.amazon.com/Hands-Graph-Neural-Networks-Python/dp/1804617520)

* Data Augmentation with Python [[Packt]](https://www.packtpub.com/product/data-augmentation-with-python/9781803246451) [[Amazon]](https://www.amazon.com/Data-Augmentation-Python-learning-augmentation/dp/1803246456)

## Get to Know the Author(s)
**Alexiei Dingli** is a professor of artificial intelligence at the University of Malta. As an AI expert with over two decades of experience, his research has helped numerous companies around the world successfully implement AI solutions. His work has been recognized globally, with international experts rating it as world-class. He is a recipient of multiple prestigious awards, including those from the European Space Agency, the World Intellectual Property Organization, and the United Nations, to name a few. With a rich collection of peer-reviewed publications to his name, he is also an esteemed member of the Malta.AI task force, which was established by the Maltese government to propel Malta to the forefront of the global AI landscape.

**David Farrugia** is a seasoned data scientist and a Ph.D. candidate in AI at the University of Malta. David Farrugia has worked in diverse industries, including gaming, manufacturing, customer relationship management, affiliate marketing, and anti-fraud. He has an interest in exploring the intersection of business and academic research. He also believes that the emerging field of neuro-symbolic AI has the potential to revolutionize the way we approach AI and solve some of the most complex problems in the world.

Neuro-Symbolic-AI

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