Patel - Hands-on artificial intelligence for search building intelligent applications and perform enterprise searches

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Devangini Patel is a PhD student at the National University of Singapore, Singapore. Her research interests include deep learning, computer vision, machine learning, and artificial intelligence. She has completed a master's in artificial intelligence at the University of Southampton, UK. She has over 5 years, experience in the field of AI and has worked on various industrial and research projects in AI, including facial expression analysis, robotics, virtual try-on, object recognition and detection, and advertisement ranking.

Nisarg Vyas is the CEO, founder, and principal engineer at InFoCusp, a consultancy firm in Ahmedabad specializing in AI projects. For the past 12 years, he has been associated with introducing AI and automated systems into mainstream products for domains such as physiological monitoring and healthcare, wearable computing, finance, recruitment and HR, e-commerce, law, defense, graphics, gaming, pharmaceuticals, and fishing. His contribution to AI for physiological monitoring was featured in the prestigious AI Magazine and acknowledged by the Association for the Advancement of AI (AAAI) as an innovative application of AI. He is the holder of several US patents, and the author of several peer-reviewed journal and conference publications.

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With the emergence of big data and modern technologies, artificial intelligence (AI) has acquired a lot of relevance in many domains. The increase in demand for automation has generated many applications for AI in fields such as robotics, predictive analytics, and finance.
This book will give you an understanding of what AI is. It explains basic search methods in detail: Depth-First Search (DFS), Breadth-First Search (BFS), and A* Search, which can be used to make intelligent decisions when the initial state, end state, and possible actions are known. Random solutions or greedy solutions can be found for such problems, but they are not optimal in terms of either space or time, and efficient approaches to space and time will be explored. We will also look at how to formulate a problem, which involves identifying its initial state, goal state, and the actions that are possible in each state. We also need to understand the data structures involved while implementing these search algorithms, because they form the basis of search exploration. Finally, we will look into what a heuristic is, because this decides the suitability of one sub-solution over another and helps you decide which step to take.

This book is for developers who are keen to get started with AI and develop practical AI-based applications. Developers who want to upgrade their normal applications to smart and intelligent versions will find this book useful. A basic knowledge and understanding of Python are assumed.

, Understanding the Depth-First Search Algorithm , practically explains the DFS algorithm with the help of a search tree. The chapter also delves into recursion, which eliminates the need to have an explicit stack.

, Understanding the Breadth-First Search Algorithm , teaches you how to traverse a graph layer-wise using a LinkedIn connection feature as an example.

, Understanding the Heuristic Search Algorithm , takes you through the priority queue data structure and explains how to visualize search trees. The chapter also covers problems related to greedy best-first search, and how A* solves that problem.