 |
4 books on AI-based Search [PDF]
Updated: May 13, 2024 | 15 |
Books on AI-based Search serve as essential references for startups focused on developing AI-driven search solutions. These resources offer a comprehensive foundation, covering various aspects of AI's role in search technology, such as natural language processing, information retrieval, relevance ranking, and personalization. They delve into advanced techniques like deep learning, semantic search, and query understanding, emphasizing the significance of AI in enhancing search accuracy and user experience. Moreover, these books often include practical examples, case studies, and best practices, enabling startups to fine-tune their AI-based search systems for optimal performance and real-world applications.
1. Google’s AI Future and What It Means For SEO’S
2023 by Goncalo Paxe Jorge Miguel
In this book, you'll delve into Google's AI future and its profound implications for SEO professionals. A consensus among leading technologists, futurists, and thought leaders is clear: AI will play an enormous role in shaping our future. Visionaries like Elon Musk have raised concerns about the potential risks associated with AI, while others highlight the transformative potential of AI in fields such as art, medicine, and science, promising to benefit humanity significantly. Regardless of their stance, there's unanimous agreement that AI's impact will be monumental.
Download PDF
2. Artificial Intelligence for .NET: Speech, Language, and Search: Building Smart Applications with Microsoft Cognitive Services APIs
2017 by Nishith Pathak
Discover the realm of artificial intelligence through this accessible and pragmatic guide, designed to help you construct applications that leverage language and user interaction for enhanced competitiveness in the modern marketplace. Explore how your application can attain a profound understanding of web content or user machine data, intelligently respond to direct user interactions via speech or text, and provide personalized recommendations for products or services. Microsoft Cognitive Services offers the tools to accomplish all this and more, with user-friendly APIs that can be integrated into desktop, web, or mobile applications. While many developers view AI implementation as a daunting task involving intricate algorithms, this book aims to alleviate those concerns by demonstrating the creation of a cognitive application with just a few lines of code. Focusing on some of the most valuable and potent language-based cognitive services APIs, "Artificial Intelligence for .NET: Speech, Language, and Search" empowers you to infuse remarkable capabilities into your applications right away. This book is suitable for developers working across various platforms, including .NET, Windows, and mobile devices, with examples provided in C#. No prior experience with AI techniques or theory is necessary.
Download PDF
3. Intelligence Emerging: Adaptivity and Search in Evolving Neural Systems
2015 by Keith L. Downing
Within the pages of this book, Keith Downing embarks on a comprehensive exploration of the often-discussed yet loosely defined notion that intelligence emerges as a phenomenon. His focus centers on neural networks, whether natural or artificial, and how their adaptability across three distinct time frames—phylogenetic (evolutionary), ontogenetic (developmental), and epigenetic (lifetime learning)—constitutes the foundation for cognitive emergence. Synthesizing insights from evolutionary biology, neuroscience, and artificial intelligence, Downing furnishes a collection of tangible instances showcasing the emergence of neurocognition. In doing so, he puts forth a fresh rationale for the broader integration of bio-inspired concepts into artificial intelligence, particularly within the subfield known as Bio-AI. A central thesis posits that two fundamental principles from traditional AI—search and representation—crucially contribute to our comprehension of emergent intelligence. The book initiates with introductory chapters elucidating five core concepts: emergent phenomena, formal search processes, representational considerations in Bio-AI, artificial neural networks (ANNs), and evolutionary algorithms (EAs). Subsequent chapters delve deeper into the realms of search, representation, and emergence within ANNs, EAs, and evolving brains.
Download PDF
4. Search in Artificial Intelligence
2012 by Leveen Kanal, Vipin Kumar
Search constitutes a fundamental element of problem-solving within artificial intelligence (AI) and the broader domains of computer science, engineering, and operations research. Various fields such as combinatorial optimization, decision analysis, game playing, learning, planning, pattern recognition, robotics, and theorem proving rely heavily on search algorithms. Not long ago, the prevailing belief in AI was that the most effective search algorithms had already been devised, leaving minimal room for further advancements. However, in recent years, numerous fresh insights and breakthroughs have emerged. New algorithms for exploring state spaces, AND/OR graph traversal, and game tree search have been uncovered. Articles covering both theoretical innovations and experimental outcomes related to backtracking, heuristic search, and constraint propagation have been disseminated. This volume compiles these recent developments in a format accessible to students and professionals keen on exploring these novel insights and findings.
Download PDF
How to download PDF:
1. Install Google Books Downloader
2. Enter Book ID to the search box and press Enter
3. Click "Download Book" icon and select PDF*
* - note that for yellow books only preview pages are downloaded
1. Google’s AI Future and What It Means For SEO’S
2023 by Goncalo Paxe Jorge Miguel
In this book, you'll delve into Google's AI future and its profound implications for SEO professionals. A consensus among leading technologists, futurists, and thought leaders is clear: AI will play an enormous role in shaping our future. Visionaries like Elon Musk have raised concerns about the potential risks associated with AI, while others highlight the transformative potential of AI in fields such as art, medicine, and science, promising to benefit humanity significantly. Regardless of their stance, there's unanimous agreement that AI's impact will be monumental.
Download PDF
2. Artificial Intelligence for .NET: Speech, Language, and Search: Building Smart Applications with Microsoft Cognitive Services APIs
2017 by Nishith Pathak
Discover the realm of artificial intelligence through this accessible and pragmatic guide, designed to help you construct applications that leverage language and user interaction for enhanced competitiveness in the modern marketplace. Explore how your application can attain a profound understanding of web content or user machine data, intelligently respond to direct user interactions via speech or text, and provide personalized recommendations for products or services. Microsoft Cognitive Services offers the tools to accomplish all this and more, with user-friendly APIs that can be integrated into desktop, web, or mobile applications. While many developers view AI implementation as a daunting task involving intricate algorithms, this book aims to alleviate those concerns by demonstrating the creation of a cognitive application with just a few lines of code. Focusing on some of the most valuable and potent language-based cognitive services APIs, "Artificial Intelligence for .NET: Speech, Language, and Search" empowers you to infuse remarkable capabilities into your applications right away. This book is suitable for developers working across various platforms, including .NET, Windows, and mobile devices, with examples provided in C#. No prior experience with AI techniques or theory is necessary.
Download PDF
3. Intelligence Emerging: Adaptivity and Search in Evolving Neural Systems
2015 by Keith L. Downing
Within the pages of this book, Keith Downing embarks on a comprehensive exploration of the often-discussed yet loosely defined notion that intelligence emerges as a phenomenon. His focus centers on neural networks, whether natural or artificial, and how their adaptability across three distinct time frames—phylogenetic (evolutionary), ontogenetic (developmental), and epigenetic (lifetime learning)—constitutes the foundation for cognitive emergence. Synthesizing insights from evolutionary biology, neuroscience, and artificial intelligence, Downing furnishes a collection of tangible instances showcasing the emergence of neurocognition. In doing so, he puts forth a fresh rationale for the broader integration of bio-inspired concepts into artificial intelligence, particularly within the subfield known as Bio-AI. A central thesis posits that two fundamental principles from traditional AI—search and representation—crucially contribute to our comprehension of emergent intelligence. The book initiates with introductory chapters elucidating five core concepts: emergent phenomena, formal search processes, representational considerations in Bio-AI, artificial neural networks (ANNs), and evolutionary algorithms (EAs). Subsequent chapters delve deeper into the realms of search, representation, and emergence within ANNs, EAs, and evolving brains.
Download PDF
4. Search in Artificial Intelligence
2012 by Leveen Kanal, Vipin Kumar
Search constitutes a fundamental element of problem-solving within artificial intelligence (AI) and the broader domains of computer science, engineering, and operations research. Various fields such as combinatorial optimization, decision analysis, game playing, learning, planning, pattern recognition, robotics, and theorem proving rely heavily on search algorithms. Not long ago, the prevailing belief in AI was that the most effective search algorithms had already been devised, leaving minimal room for further advancements. However, in recent years, numerous fresh insights and breakthroughs have emerged. New algorithms for exploring state spaces, AND/OR graph traversal, and game tree search have been uncovered. Articles covering both theoretical innovations and experimental outcomes related to backtracking, heuristic search, and constraint propagation have been disseminated. This volume compiles these recent developments in a format accessible to students and professionals keen on exploring these novel insights and findings.
Download PDF
How to download PDF:
1. Install Google Books Downloader
2. Enter Book ID to the search box and press Enter
3. Click "Download Book" icon and select PDF*
* - note that for yellow books only preview pages are downloaded
