Видавець: Packt Publishing
Lovisa Johansson, David Dossot
RabbitMQ is an open source message queuing software that acts as a message broker using the Advanced Message Queuing Protocol (AMQP). This book will help you to get to grips with RabbitMQ to build your own applications with a message queue architecture. You’ll learn from the experts from CloudAMQP as they share what they've learned while managing the largest fleet of RabbitMQ clusters in the world.Following the case study of Complete Car, you’ll discover how you can use RabbitMQ to provide exceptional customer service and user experience, and see how a message queue architecture makes it easy to upgrade the app and add features as the company grows. From implementing simple synchronous operations through to advanced message routing and tracking, you’ll explore how RabbitMQ streamlines scalable operations for fast distribution. This book will help you understand the advantages of message queue architecture, including application scalability, resource efficiency, and user reliability. Finally, you’ll learn best practices for working with RabbitMQ and be able to use this book as a reference guide for your future app development projects.By the end of this book, you’ll have learned how to use message queuing software to streamline the development of your distributed and scalable applications.
David Dossot
This book is a quick and concise introduction to RabbitMQ. Follow the unique case study of Clever Coney Media as they progressively discover how to fully utilize RabbitMQ, containing clever examples and detailed explanations. Whether you are someone who develops enterprise messaging products professionally or a hobbyist who is already familiar with open source Message Queuing software and you are looking for a new challenge, then this is the book for you. Although you should be familiar with Java, Ruby, and Python to get the most out of the examples, RabbitMQ Essentials will give you the push you need to get started that no other RabbitMQ tutorial can provide you with.
Jia Huang
Most developers can spin up a RAG pipeline in an afternoon using LangChain or LlamaIndex. Far fewer understand why retrieval fails or how to fix it. This book is for those who want to go deeper.'RAG From First Principles' dismantles the retrieval-augmented generation stack layer by layer, how documents are ingested and parsed, why chunking strategy directly impacts answer quality, how embedding models encode meaning, what happens inside a vector database, and how sparse and dense retrieval interact in a hybrid system. Written by Jia Huang, a research engineer and bestselling AI author, it brings research depth and production experience to one of AI's most critical engineering disciplines.Structured as a progressive dialogue between a seasoned engineer and two students, the book surfaces the questions practitioners actually ask. Each chapter builds on the last, from data import and chunking through embedding selection, index design, hybrid search, and post-retrieval processing, into response generation, evaluation, and advanced paradigms including GraphRAG, Agentic RAG, and Modular RAG.By the end, you'll have the architectural understanding to optimize, debug, and extend your RAG systems with confidence.
Denis Rothman
RAG-Driven Generative AI provides a roadmap for building effective LLM, computer vision, and generative AI systems that balance performance and costs.This book offers a detailed exploration of RAG and how to design, manage, and control multimodal AI pipelines. By connecting outputs to traceable source documents, RAG improves output accuracy and contextual relevance, offering a dynamic approach to managing large volumes of information. This AI book shows you how to build a RAG framework, providing practical knowledge on vector stores, chunking, indexing, and ranking. You’ll discover techniques to optimize your project’s performance and better understand your data, including using adaptive RAG and human feedback to refine retrieval accuracy, balancing RAG with fine-tuning, implementing dynamic RAG to enhance real-time decision-making, and visualizing complex data with knowledge graphs.You’ll be exposed to a hands-on blend of frameworks like LlamaIndex and Deep Lake, vector databases such as Pinecone and Chroma, and models from Hugging Face and OpenAI. By the end of this book, you will have acquired the skills to implement intelligent solutions, keeping you competitive in fields from production to customer service across any project.*Email sign-up and proof of purchase required
Denis Rothman
Stop moving your data to the AI. This second edition defines a revolutionary architectural shift: bringing the AI to the data. By using Oracle Database 23ai as a converged engine in this book, you will architect Sovereign AI systems that eliminate the fragmentation, latency, and massive security risks inherent in traditional data extraction.You’ll work with DualRAG, synchronizing unstructured vector semantics with the deterministic truth of structured SQL, Graph, and Spatial retrieval. This allows your systems to reason over verified corporate data rather than probabilistic guesses, reducing hallucinations at the source. Moving beyond simple pipelines, you’ll also build MAS-RAG (multi-agent systems for RAG), where autonomous agents coordinate across hybrid retrieval workflows, multimodal video pipelines, and graph-based knowledge structures.Designed for developers and architects, these blueprints transform disconnected data silos into a unified engine to architect autonomous enterprise intelligence that scales with RLHF and model fine-tuning. By the end of the book, you’ll be able to design and deploy enterprise AI systems that combine retrieval, reasoning, and structured data to build reliable generative AI applications.*Email sign-up and proof of purchase required
Andrey Koleshko
A step-by-step and interactive approach explaining the Rake essentials along with code examples and advanced features. If you are a developer who is acquainted with the Ruby language and want to speed up writing the code concerned with files, then this book is for you. To start reading this book, basic Ruby knowledge is required; however, a huge amount of experience with the language is not necessary.
Rancher Deep Dive. Manage enterprise Kubernetes seamlessly with Rancher
Matthew Mattox
Knowing how to use Rancher enables you to manage multiple clusters and applications without being locked into a vendor’s platform. This book will guide you through Rancher’s capabilities while deepening your understanding of Kubernetes and helping you to take your applications to a new level.The book begins by introducing you to Rancher and Kubernetes, helping you to learn and implement best practices. As you progress through the chapters, you’ll understand the strengths and limitations of Rancher and Kubernetes and discover all the different ways to deploy Rancher. You’ll also find out how to design and deploy Kubernetes clusters to match your requirements. The concluding chapters will show you how to set up a continuous integration and continuous deployment (CI/CD) pipeline for deploying applications into a Rancher cluster, along with covering supporting services such as image registries and Helm charts.By the end of this Kubernetes book, you’ll be able to confidently deploy your mission-critical production workloads on Rancher-managed Kubernetes clusters.
Rapid - Apache Mahout Clustering designs. Explore clustering algorithms used with Apache Mahout
Ashish Gupta
As more and more organizations are discovering the use of big data analytics, interest in platforms that provide storage, computation, and analytic capabilities has increased. Apache Mahout caters to this need and paves the way for the implementation of complex algorithms in the field of machine learning to better analyse your data and get useful insights into it.Starting with the introduction of clustering algorithms, this book provides an insight into Apache Mahout and different algorithms it uses for clustering data. It provides a general introduction of the algorithms, such as K-Means, Fuzzy K-Means, StreamingKMeans, and how to use Mahout to cluster your data using a particular algorithm. You will study the different types of clustering and learn how to use Apache Mahout with real world data sets to implement and evaluate your clusters.This book will discuss about cluster improvement and visualization using Mahout APIs and also explore model-based clustering and topic modelling using Dirichlet process. Finally, you will learn how to build and deploy a model for production use.