Vector Database
DOWNLOAD
Download Vector Database PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Vector Database book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Vector Database
DOWNLOAD
Author : Richard Johnson
language : en
Publisher: HiTeX Press
Release Date : 2025-06-16
Vector Database written by Richard Johnson and has been published by HiTeX Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-16 with Computers categories.
"Vector Database" Vector Database is a comprehensive and authoritative guide to the cutting-edge world of high-dimensional search and retrieval. This book begins by grounding readers in the theoretical foundations—tracing the journey from traditional databases to the latest innovations in vector search, and unpacking the underlying mathematics, embedding methodologies, and the diverse modalities of data that vector databases support. Through crisp explanations and illustrative examples, it demystifies how vector representations power modern machine learning systems and unlock new capabilities for handling complex, unstructured information. A major focus of the book is on the practical engineering behind vector data: from algorithmic approaches (like approximate nearest neighbor search, advanced indexing structures, and hybrid queries) to the full lifecycle of data ingestion, transformation, versioning, and update management. Readers are guided through distributed architectures, sharding strategies, fault-tolerance, and cloud-native deployment patterns—arming practitioners with actionable insights into scaling, managing, and optimizing vector systems for enterprise-grade reliability and performance. Security, privacy, and compliance best practices are also rigorously addressed, ensuring readiness for production use in regulated environments. Finally, Vector Database explores the pivotal role of vector search within modern AI and analytics ecosystems. It covers seamless integration with machine learning pipelines, MLOps, developer tooling, and interoperability with traditional data stores. Advanced and forward-looking chapters discuss trillion-scale collections, operational observability, benchmarking, and the fusion of graph, symbolic, and vector paradigms. Whether you are a researcher, engineer, or technical leader, this volume is an essential resource for mastering the foundational principles and practical tools shaping the future of intelligent data retrieval.
Vector Databases For Generative Ai Applications
DOWNLOAD
Author : Anand Vemula
language : en
Publisher: Anand Vemula
Release Date :
Vector Databases For Generative Ai Applications written by Anand Vemula and has been published by Anand Vemula this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.
"Vector Databases for Generative AI Applications" explores the intersection of two cutting-edge fields: vector databases and generative artificial intelligence (AI). The book provides a comprehensive overview of how vector databases, a specialized form of database optimized for vector similarity search, can enhance various generative AI applications. The first part of the book introduces the fundamentals of vector databases, including key concepts such as vector indexing, similarity search algorithms, and performance optimizations. Readers are guided through the architecture and functionality of vector databases, with a focus on how they differ from traditional relational databases and their suitability for handling high-dimensional data. In the second part, the book delves into the application of vector databases in generative AI. It explores how vector databases can be leveraged to store and retrieve large collections of high-dimensional vectors, which are prevalent in generative AI tasks such as natural language processing, computer vision, and recommender systems. Through real-world examples and case studies, the book demonstrates how vector databases can accelerate the training and inference processes of generative AI models by efficiently managing vector representations of data points. Moreover, the book addresses the challenges and considerations involved in integrating vector databases with generative AI frameworks and platforms. It discusses topics such as data preprocessing, indexing strategies, distributed computing, and scalability, providing practical guidance for architects and developers looking to deploy vector databases in their generative AI pipelines. Throughout the book, the authors highlight the synergies between vector databases and generative AI, showcasing how the combination of these technologies can enable breakthroughs in applications such as content generation, personalized recommendations, and data synthesis. By offering both theoretical insights and hands-on implementation techniques, "Vector Databases for Generative AI Applications" serves as a valuable resource for researchers, practitioners, and enthusiasts seeking to harness the power of vector databases to drive innovation in generative AI.
Mastering Vector Databases
DOWNLOAD
Author : Robert Johnson
language : en
Publisher: HiTeX Press
Release Date : 2025-01-03
Mastering Vector Databases written by Robert Johnson and has been published by HiTeX Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-03 with Computers categories.
"Mastering Vector Databases: The Future of Data Retrieval and AI" offers an insightful exploration into the transformative world of vector databases, a cutting-edge technology pivotal to advancing data management and artificial intelligence applications. This book is meticulously designed to impart a comprehensive understanding, beginning with foundational concepts and advancing to intricate techniques, ensuring readers develop the expertise necessary to leverage vector databases effectively. Throughout its pages, it demystifies core concepts, illustrating how vector databases efficiently handle high-dimensional data, optimize query processes, and integrate with AI systems to enhance performance across diverse applications. In an era where data drives decision-making, this book serves as an essential resource for computer scientists, IT professionals, and data enthusiasts eager to stay at the forefront of technology. It delves into real-world applications ranging from recommendation systems to image retrieval, underscoring the practical benefits and industry impact of vector databases. Moreover, it addresses challenges in scalability, security, and privacy, providing readers with a robust framework for implementing secure and efficient data solutions. "Mastering Vector Databases" is your guide to navigating the complexities of modern data environments, empowering you to harness the full potential of this innovative technology.
New Trends In Database And Information Systems
DOWNLOAD
Author : Joe Tekli
language : en
Publisher: Springer Nature
Release Date : 2024-11-16
New Trends In Database And Information Systems written by Joe Tekli and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-16 with Computers categories.
This book constitutes short papers, Doctoral Consortium and Workshops papers which were held in conjunction with the 28th European Conference on New Trends in Databases and Information Systems, ADBIS 2024, which took place in Bayonne, France, during August 28–31, 2024. The total of 28 full papers and 7 short papers presented in this book were carefully reviewed and selected from 103 submissions. They were organized in the following topical sections: Doctoral Consortium; 5th Workshop on Intelligent Data - From Data to Knowledge (DOING 2024); 3rd Workshop on Knowledge Graphs Analysis on a Large Scale (K-GALS 2024); 6th Workshop on Modern Approaches in Data Engineering and Information System Design (MADEISD 2024); 3rd Workshop on Personalization and Recommender Systems (PERS 2024); Access methods and query processing; discovery and data analysis; Machine Learning; large language models; and tutorials.
Database Design And Modeling With Google Cloud
DOWNLOAD
Author : Abirami Sukumaran
language : en
Publisher: Packt Publishing Ltd
Release Date : 2023-12-29
Database Design And Modeling With Google Cloud written by Abirami Sukumaran and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-29 with Computers categories.
Build faster and efficient real-world applications on the cloud with a fitting database model that's perfect for your needs Key Features Familiarize yourself with business and technical considerations involved in modeling the right database Take your data to applications, analytics, and AI with real-world examples Learn how to code, build, and deploy end-to-end solutions with expert advice Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionIn the age of lightning-speed delivery, customers want everything developed, built, and delivered at high speed and at scale. Knowledge, design, and choice of database is critical in that journey, but there is no one-size-fits-all solution. This book serves as a comprehensive and practical guide for data professionals who want to design and model their databases efficiently. The book begins by taking you through business, technical, and design considerations for databases. Next, it takes you on an immersive structured database deep dive for both transactional and analytical real-world use cases using Cloud SQL, Spanner, and BigQuery. As you progress, you’ll explore semi-structured and unstructured database considerations with practical applications using Firestore, cloud storage, and more. You’ll also find insights into operational considerations for databases and the database design journey for taking your data to AI with Vertex AI APIs and generative AI examples. By the end of this book, you will be well-versed in designing and modeling data and databases for your applications using Google Cloud.What you will learn Understand different use cases and real-world applications of data in the cloud Work with document and indexed NoSQL databases Get to grips with modeling considerations for analytics, AI, and ML Use real-world examples to learn about ETL services Design structured, semi-structured, and unstructured data for your applications and analytics Improve observability, performance, security, scalability, latency SLAs, SLIs, and SLOs Who this book is for This book is for database developers, data engineers, and architects looking to design, model, and build database applications on the cloud with an extended focus on operational consideration and taking their data to AI. Data scientists, as well ML and AI engineers who want to use Google Cloud services in the data to AI journey will also find plenty of useful information in this book. It will also be useful to data analysts and BI developers who want to use SQL impactfully to generate ML and generative AI insights from their data.
Building Ai Intensive Python Applications
DOWNLOAD
Author : Rachelle Palmer
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-09-06
Building Ai Intensive Python Applications written by Rachelle Palmer and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-06 with Computers categories.
Master retrieval-augmented generation architecture and fine-tune your AI stack, along with discovering real-world use cases and best practices to create powerful AI apps Key Features Get to grips with the fundamentals of LLMs, vector databases, and Python frameworks Implement effective retrieval-augmented generation strategies with MongoDB Atlas Optimize AI models for performance and accuracy with model compression and deployment optimization Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionThe era of generative AI is upon us, and this book serves as a roadmap to harness its full potential. With its help, you’ll learn the core components of the AI stack: large language models (LLMs), vector databases, and Python frameworks, and see how these technologies work together to create intelligent applications. The chapters will help you discover best practices for data preparation, model selection, and fine-tuning, and teach you advanced techniques such as retrieval-augmented generation (RAG) to overcome common challenges, such as hallucinations and data leakage. You’ll get a solid understanding of vector databases, implement effective vector search strategies, refine models for accuracy, and optimize performance to achieve impactful results. You’ll also identify and address AI failures to ensure your applications deliver reliable and valuable results. By evaluating and improving the output of LLMs, you’ll be able to enhance their performance and relevance. By the end of this book, you’ll be well-equipped to build sophisticated AI applications that deliver real-world value.What you will learn Understand the architecture and components of the generative AI stack Explore the role of vector databases in enhancing AI applications Master Python frameworks for AI development Implement Vector Search in AI applications Find out how to effectively evaluate LLM output Overcome common failures and challenges in AI development Who this book is for This book is for software engineers and developers looking to build intelligent applications using generative AI. While the book is suitable for beginners, a basic understanding of Python programming is required to make the most of it.
Cloud Innovation Scaling With Vectors And Llms
DOWNLOAD
Author : Sayantan Bhattacharyya
language : en
Publisher: Libertatem Media Private Limited
Release Date : 2024-09-11
Cloud Innovation Scaling With Vectors And Llms written by Sayantan Bhattacharyya and has been published by Libertatem Media Private Limited this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-11 with Business & Economics categories.
Cloud-native architectures have become the foundation for modern enterprises seeking agility, scalability, and efficiency. Cloud Innovation: Scaling with Vectors and LLMs is a definitive guide for IT leaders, solution architects, and senior managers aiming to integrate advanced technologies like vector databases and Large Language Models (LLMs) into scalable cloud systems. This book explores the principles of cloud-native systems, providing actionable insights into designing elastic and resilient architectures. Readers will learn how to leverage vector databases for high-dimensional data management and harness the power of LLMs for natural language understanding and generation. From optimizing real-time data ingestion to implementing retrieval-augmented generation (RAG) systems, the book offers practical strategies for building future-ready applications. Key topics include the integration of LLMs with vector databases, techniques for elastic scaling, cost optimization strategies, and designing systems for high availability and disaster recovery. Real-world case studies demonstrate how leading enterprises have successfully deployed these technologies to drive innovation, enhance operational efficiency, and meet evolving customer needs. Packed with insights on security, compliance, and performance optimization, Cloud Innovation also examines emerging trends in cloud computing and AI, preparing professionals to navigate the next wave of digital transformation. Whether you ' re modernizing legacy systems or pioneering AI-driven solutions, this book equips you with the tools to scale efficiently, innovate boldly, and lead in the rapidly evolving cloud ecosystem.
A Simple Guide To Retrieval Augmented Generation
DOWNLOAD
Author : Abhinav Kimothi
language : en
Publisher: Simon and Schuster
Release Date : 2025-07-01
A Simple Guide To Retrieval Augmented Generation written by Abhinav Kimothi and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-01 with Computers categories.
Everything you need to know about Retrieval Augmented Generation in one human-friendly guide. Augmented Generation—or RAG—enhances an LLM’s available data by adding context from an external knowledge base, so it can answer accurately about proprietary content, recent information, and even live conversations. RAG is powerful, and with A Simple Guide to Retrieval Augmented Generation, it’s also easy to understand and implement! In A Simple Guide to Retrieval Augmented Generation you’ll learn: • The components of a RAG system • How to create a RAG knowledge base • The indexing and generation pipeline • Evaluating a RAG system • Advanced RAG strategies • RAG tools, technologies, and frameworks A Simple Guide to Retrieval Augmented Generation gives an easy, yet comprehensive, introduction to RAG for AI beginners. You’ll go from basic RAG that uses indexing and generation pipelines, to modular RAG and multimodal data from images, spreadsheets, and more. About the Technology If you want to use a large language model to answer questions about your specific business, you’re out of luck. The LLM probably knows nothing about it and may even make up a response. Retrieval Augmented Generation is an approach that solves this class of problems. The model first retrieves the most relevant pieces of information from your knowledge stores (search index, vector database, or a set of documents) and then generates its answer using the user’s prompt and the retrieved material as context. This avoids hallucination and lets you decide what it says. About the Book A Simple Guide to Retrieval Augmented Generation is a plain-English guide to RAG. The book is easy to follow and packed with realistic Python code examples. It takes you concept-by-concept from your first steps with RAG to advanced approaches, exploring how tools like LangChain and Python libraries make RAG easy. And to make sure you really understand how RAG works, you’ll build a complete system yourself—even if you’re new to AI! What’s Inside • RAG components and applications • Evaluating RAG systems • Tools and frameworks for implementing RAG About the Readers For data scientists, engineers, and technology managers—no prior LLM experience required. Examples use simple, well-annotated Python code. About the Author Abhinav Kimothi is a seasoned data and AI professional. He has spent over 15 years in consulting and leadership roles in data science, machine learning and AI, and currently works as a Director of Data Science at Sigmoid. Table of Contents Part 1 1 LLMs and the need for RAG 2 RAG systems and their design Part 2 3 Indexing pipeline: Creating a knowledge base for RAG 4 Generation pipeline: Generating contextual LLM responses 5 RAG evaluation: Accuracy, relevance, and faithfulness Part 3 6 Progression of RAG systems: Naïve, advanced, and modular RAG 7 Evolving RAGOps stack Part 4 8 Graph, multimodal, agentic, and other RAG variants 9 RAG development framework and further exploration
Chatgpt For Conversational Ai And Chatbots
DOWNLOAD
Author : Adrian Thompson
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-07-30
Chatgpt For Conversational Ai And Chatbots written by Adrian Thompson and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-30 with Computers categories.
Explore ChatGPT technologies to create state-of-the-art chatbots and voice assistants, and prepare to lead the AI revolution Key Features Learn how to leverage ChatGPT to create innovative conversational AI solutions for your organization Harness LangChain and delve into step-by-step LLM application development for conversational AI Gain insights into security, privacy, and the future landscape of large language models and conversational AI Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionChatGPT for Conversational AI and Chatbots is a definitive resource for exploring conversational AI, ChatGPT, and large language models. This book introduces the fundamentals of ChatGPT and conversational AI automation. You’ll explore the application of ChatGPT in conversation design, the use of ChatGPT as a tool to create conversational experiences, and a range of other practical applications. As you progress, you’ll delve into LangChain, a dynamic framework for LLMs, covering topics such as prompt engineering, chatbot memory, using vector stores, and validating responses. Additionally, you’ll learn about creating and using LLM-enabling tools, monitoring and fine tuning, LangChain UI tools such as LangFlow, and the LangChain ecosystem. You’ll also cover popular use cases, such as using ChatGPT in conjunction with your own data. Later, the book focuses on creating a ChatGPT-powered chatbot that can comprehend and respond to queries directly from your unique data sources. The book then guides you through building chatbot UIs with ChatGPT API and some of the tools and best practices available. By the end of this book, you’ll be able to confidently leverage ChatGPT technologies to build conversational AI solutions.What you will learn Gain a solid understanding of ChatGPT and its capabilities and limitations Understand how to use ChatGPT for conversation design Discover how to use advanced LangChain techniques, such as prompting, memory, agents, chains, vector stores, and tools Create a ChatGPT chatbot that can answer questions about your own data Develop a chatbot powered by ChatGPT API Explore the future of conversational AI, LLMs, and ChatGPT alternatives Who this book is for This book is for tech-savvy readers, conversational AI practitioners, engineers, product owners, business analysts, and entrepreneurs wanting to integrate ChatGPT into conversational experiences and explore the possibilities of this game-changing technology. Anyone curious about using internal data with ChatGPT and looking to stay up to date with the developments in large language models will also find this book helpful. Some expertise in coding and standard web design concepts would be useful, along with familiarity with conversational AI terminology, though not essential.
Enterprise Semantic Search Revolutionizes Business Conversations
DOWNLOAD
Author : Jothi Periasamy
language : en
Publisher: LLM ARTIFICIAL INTELLIGENCE INDIA PRIVATE LIMITED
Release Date : 2024-11-27
Enterprise Semantic Search Revolutionizes Business Conversations written by Jothi Periasamy and has been published by LLM ARTIFICIAL INTELLIGENCE INDIA PRIVATE LIMITED this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-27 with Computers categories.
Discover the transformative power of enterprise semantic search without relying on Large Language Models (LLMs) in "Enterprise Semantic Search revolutionizes business conversation" - This comprehensive guide explores the innovative techniques behind implementing semantic search at scale across diverse data types—text, images, audio, and video—empowering organizations to achieve more meaningful, intent-driven conversations. Authored by leading academics and industry professionals, this book covers vector databases, embeddings, multidimensional modeling, algorithms, and cloud technologies. A practical framework is presented that can be used to build advanced semantic search systems. Discover how to converge enterprise data and develop AI-powered tools for secure, dynamic, and user-friendly searches. Key highlights include: ● Understanding vectors, embeddings, and their roles in semantic search. ● Implementing independent and unified search across varied data formats. ● Leveraging cutting-edge technologies like Sentence-BERT, CLIP, Pinecone, Cloud Technologies, and more. ● Real-world applications showcasing enhanced product discoverability, personalization, and decision-making. Whether you're an AI enthusiast, data scientist, developer, or enterprise leader, this book offers hands-on guidance, source code, and reference architectures to simplify implementation while accelerating results. Step into the future of intelligent search systems and unlock the full potential of your data.