Introduction to Graph Intelligence
Mohamed Abdel‐Basset, Nour Moustafa, Hossam Hawash, Zahir Tari · 2023
Deep learning refers to a category of machine learning methods, which is based on the concept of artificial neural networks. In fact, the majority of the essential building components of deep learning have existed for decades though deep learning has only recently gained popularity. This chapter provides an introduction to graph intelligence as well as the concepts related to deep learning. Then, it presents the background of deep learning by reviewing elementary deep learning models such as feedforward networks, convolutional neural networks, recurrent neural networks, transformer networks, and autoencoders. The chapter then debates the backpropagation methods and related tricks for training deep networks. By the end of this chapter, we briefly discuss the main content covered in each chapter of the book to give the reader concise insight into the systematic flow of topics across chapters.