Unlocking Data With Generative Ai And Rag

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Unlocking Data With Generative Ai And Rag

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Author : Keith Bourne
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-09-27

Unlocking Data With Generative Ai And Rag written by Keith Bourne 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 2024-09-27 with Computers categories.

Leverage cutting-edge generative AI techniques such as RAG to realize the potential of your data and drive innovation as well as gain strategic advantage Key Features Optimize data retrieval and generation using vector databases Boost decision-making and automate workflows with AI agents Overcome common challenges in implementing real-world RAG systems Purchase of the print or Kindle book includes a free PDF eBook Book Description Generative AI is helping organizations tap into their data in new ways, with retrieval-augmented generation (RAG) combining the strengths of large language models (LLMs) with internal data for more intelligent and relevant AI applications. The author harnesses his decade of ML experience in this book to equip you with the strategic insights and technical expertise needed when using RAG to drive transformative outcomes. The book explores RAG’s role in enhancing organizational operations by blending theoretical foundations with practical techniques. You’ll work with detailed coding examples using tools such as LangChain and Chroma’s vector database to gain hands-on experience in integrating RAG into AI systems. The chapters contain real-world case studies and sample applications that highlight RAG’s diverse use cases, from search engines to chatbots. You’ll learn proven methods for managing vector databases, optimizing data retrieval, effective prompt engineering, and quantitatively evaluating performance. The book also takes you through advanced integrations of RAG with cutting-edge AI agents and emerging non-LLM technologies. By the end of this book, you’ll be able to successfully deploy RAG in business settings, address common challenges, and push the boundaries of what’s possible with this revolutionary AI technique. What you will learn Understand RAG principles and their significance in generative AI Integrate LLMs with internal data for enhanced operations Master vectorization, vector databases, and vector search techniques Develop skills in prompt engineering specific to RAG and design for precise AI responses Familiarize yourself with AI agents' roles in facilitating sophisticated RAG applications Overcome scalability, data quality, and integration issues Discover strategies for optimizing data retrieval and AI interpretability Who this book is for This book is for AI researchers, data scientists, software developers, and business analysts looking to leverage RAG and generative AI to enhance data retrieval, improve AI accuracy, and drive innovation. It is particularly suited for anyone with a foundational understanding of AI who seeks practical, hands-on learning. The book offers real-world coding examples and strategies for implementing RAG effectively, making it accessible to both technical and non-technical audiences. A basic understanding of Python and Jupyter Notebooks is required.

Llm Design Patterns

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Author : Ken Huang
language : en
Publisher: Packt Publishing Ltd
Release Date : 2025-05-30

Llm Design Patterns written by Ken Huang 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 2025-05-30 with Computers categories.

Explore reusable design patterns, including data-centric approaches, model development, model fine-tuning, and RAG for LLM application development and advanced prompting techniques Key Features Learn comprehensive LLM development, including data prep, training pipelines, and optimization Explore advanced prompting techniques, such as chain-of-thought, tree-of-thought, RAG, and AI agents Implement evaluation metrics, interpretability, and bias detection for fair, reliable models Print or Kindle purchase includes a free PDF eBook Book DescriptionThis practical guide for AI professionals enables you to build on the power of design patterns to develop robust, scalable, and efficient large language models (LLMs). Written by a global AI expert and popular author driving standards and innovation in Generative AI, security, and strategy, this book covers the end-to-end lifecycle of LLM development and introduces reusable architectural and engineering solutions to common challenges in data handling, model training, evaluation, and deployment. You’ll learn to clean, augment, and annotate large-scale datasets, architect modular training pipelines, and optimize models using hyperparameter tuning, pruning, and quantization. The chapters help you explore regularization, checkpointing, fine-tuning, and advanced prompting methods, such as reason-and-act, as well as implement reflection, multi-step reasoning, and tool use for intelligent task completion. The book also highlights Retrieval-Augmented Generation (RAG), graph-based retrieval, interpretability, fairness, and RLHF, culminating in the creation of agentic LLM systems. By the end of this book, you’ll be equipped with the knowledge and tools to build next-generation LLMs that are adaptable, efficient, safe, and aligned with human values. What you will learn Implement efficient data prep techniques, including cleaning and augmentation Design scalable training pipelines with tuning, regularization, and checkpointing Optimize LLMs via pruning, quantization, and fine-tuning Evaluate models with metrics, cross-validation, and interpretability Understand fairness and detect bias in outputs Develop RLHF strategies to build secure, agentic AI systems Who this book is for This book is essential for AI engineers, architects, data scientists, and software engineers responsible for developing and deploying AI systems powered by large language models. A basic understanding of machine learning concepts and experience in Python programming is a must.

Artificial Intelligence For Cybersecurity

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Author : Bojan Kolosnjaji
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-10-31

Artificial Intelligence For Cybersecurity written by Bojan Kolosnjaji 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 2024-10-31 with Computers categories.

Gain well-rounded knowledge of AI methods in cybersecurity and obtain hands-on experience in implementing them to bring value to your organization Key Features Familiarize yourself with AI methods and approaches and see how they fit into cybersecurity Learn how to design solutions in cybersecurity that include AI as a key feature Acquire practical AI skills using step-by-step exercises and code examples Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionArtificial intelligence offers data analytics methods that enable us to efficiently recognize patterns in large-scale data. These methods can be applied to various cybersecurity problems, from authentication and the detection of various types of cyberattacks in computer networks to the analysis of malicious executables. Written by a machine learning expert, this book introduces you to the data analytics environment in cybersecurity and shows you where AI methods will fit in your cybersecurity projects. The chapters share an in-depth explanation of the AI methods along with tools that can be used to apply these methods, as well as design and implement AI solutions. You’ll also examine various cybersecurity scenarios where AI methods are applicable, including exercises and code examples that’ll help you effectively apply AI to work on cybersecurity challenges. The book also discusses common pitfalls from real-world applications of AI in cybersecurity issues and teaches you how to tackle them. By the end of this book, you’ll be able to not only recognize where AI methods can be applied, but also design and execute efficient solutions using AI methods.What you will learn Recognize AI as a powerful tool for intelligence analysis of cybersecurity data Explore all the components and workflow of an AI solution Find out how to design an AI-based solution for cybersecurity Discover how to test various AI-based cybersecurity solutions Evaluate your AI solution and describe its advantages to your organization Avoid common pitfalls and difficulties when implementing AI solutions Who this book is for This book is for machine learning practitioners looking to apply their skills to overcome cybersecurity challenges. Cybersecurity workers who want to leverage machine learning methods will also find this book helpful. Fundamental concepts of machine learning and beginner-level knowledge of Python programming are needed to understand the concepts present in this book. Whether you’re a student or an experienced professional, this book offers a unique and valuable learning experience that will enable you to protect your network and data against the ever-evolving threat landscape.

Proceedings Of International Conference On Paradigms Of Communication Computing And Data Analytics

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Author : Himanshu Mittal
language : en
Publisher: Springer Nature
Release Date : 2025-01-26

Proceedings Of International Conference On Paradigms Of Communication Computing And Data Analytics written by Himanshu Mittal and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-26 with Computers categories.

This book is a collection of selected high-quality research papers presented at the International Conference on Paradigms of Communication, Computing and Data Analytics (PCCDA 2024), held at Pt. Lalit Mohan Sharma Campus, Rishikesh, Sri Dev Suman Uttarakhand University, Uttarakhand, India, during 20–21 April 2024. It discusses cutting-edge research in the areas of advanced computing, communications and data science techniques. The book is a collection of the latest research articles in computation algorithm, communication and data sciences, intertwined with each other for efficiency.

Databricks Data Intelligence Platform

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Author : Nikhil Gupta
language : en
Publisher: Springer Nature
Release Date : 2024-10-12

Databricks Data Intelligence Platform written by Nikhil Gupta and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-12 with Computers categories.

This book is your comprehensive guide to building robust Generative AI solutions using the Databricks Data Intelligence Platform. Databricks is the fastest-growing data platform offering unified analytics and AI capabilities within a single governance framework, enabling organizations to streamline their data processing workflows, from ingestion to visualization. Additionally, Databricks provides features to train a high-quality large language model (LLM), whether you are looking for Retrieval-Augmented Generation (RAG) or fine-tuning. Databricks offers a scalable and efficient solution for processing large volumes of both structured and unstructured data, facilitating advanced analytics, machine learning, and real-time processing. In today's GenAI world, Databricks plays a crucial role in empowering organizations to extract value from their data effectively, driving innovation and gaining a competitive edge in the digital age. This book will not only help you master the Data Intelligence Platform but also help power your enterprise to the next level with a bespoke LLM unique to your organization. Beginning with foundational principles, the book starts with a platform overview and explores features and best practices for ingestion, transformation, and storage with Delta Lake. Advanced topics include leveraging Databricks SQL for querying and visualizing large datasets, ensuring data governance and security with Unity Catalog, and deploying machine learning and LLMs using Databricks MLflow for GenAI. Through practical examples, insights, and best practices, this book equips solution architects and data engineers with the knowledge to design and implement scalable data solutions, making it an indispensable resource for modern enterprises. Whether you are new to Databricks and trying to learn a new platform, a seasoned practitioner building data pipelines, data science models, or GenAI applications, or even an executive who wants to communicate the value of Databricks to customers, this book is for you. With its extensive feature and best practice deep dives, it also serves as an excellent reference guide if you are preparing for Databricks certification exams. What You Will Learn Foundational principles of Lakehouse architecture Key features including Unity Catalog, Databricks SQL (DBSQL), and Delta Live Tables Databricks Intelligence Platform and key functionalities Building and deploying GenAI Applications from data ingestion to model serving Databricks pricing, platform security, DBRX, and many more topics Who This Book Is For Solution architects, data engineers, data scientists, Databricks practitioners, and anyone who wants to deploy their Gen AI solutions with the Data Intelligence Platform. This is also a handbook for senior execs who need to communicate the value of Databricks to customers. People who are new to the Databricks Platform and want comprehensive insights will find the book accessible.

Ultimate Snowflake Cortex Ai For Generative Ai Applications Design Build And Deploy Generative Ai Solutions With Snowflake Cortex For Real World And Industry Scale Applications

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Author : Krishnan Srinivasan
language : en
Publisher: Orange Education Pvt Limited
Release Date : 2025-06-21

Ultimate Snowflake Cortex Ai For Generative Ai Applications Design Build And Deploy Generative Ai Solutions With Snowflake Cortex For Real World And Industry Scale Applications written by Krishnan Srinivasan and has been published by Orange Education Pvt Limited this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-21 with Computers categories.

Power your AI Journey and Build the Future with Snowflake Cortex. Key Features● Build enterprise-ready GenAI apps using Snowflake Cortex tools and APIs.● Implement RAG, AI Agents, and Document AI with real-world precision.● Explore practical Cortex use cases across industries and domains. Book DescriptionSnowflake Cortex is redefining how modern enterprises build, scale, and deploy Generative AI—natively within the data cloud. Ultimate Snowflake Cortex AI for Generative AI Applications is a hands-on, end-to-end guide designed for data professionals, engineers, and technical leaders eager to unlock the full power of Snowflake’s native AI engine. The book begins by grounding you in the fundamentals of AI/ML within the Snowflake ecosystem before diving deep into the architecture, capabilities, and use cases of Snowflake Cortex. As you progress, you’ll explore Cortex’s built-in machine learning functions, dive into prompt engineering, Retrieval-Augmented Generation (RAG), and learn how to leverage LLM functions effectively. You'll gain hands-on experience in fine-tuning models, translating natural language queries into actionable insights, and automating document processing using Cortex’s Document AI. Practical chapters on security, governance, and cost discipline ensure you're prepared for enterprise-scale AI deployment. With real-world case studies and cross-industry applications, this book equips you with both the strategic understanding and technical skills to implement Generative AI at scale. Cortex is the future of enterprise AI—don’t just adapt to it, lead it. What you will learn● Build and deploy Generative AI apps using Snowflake Cortex.● Understand and apply Cortex's built-in LLM functions effectively.● Fine-tune LLMs for domain-specific, enterprise-grade applications.● Use RAG and prompt engineering for accurate AI responses.● Extract insights from structured and unstructured enterprise data.● Automate document workflows using Cortex’s Document AI features.● Solve cross-industry problems with real-world Cortex implementations.

Rag In Action Building The Future Of Ai Driven Applications

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Author : Srinivasan Ramalingam
language : en
Publisher: Libertatem Media Private Limited
Release Date : 2023-12-08

Rag In Action Building The Future Of Ai Driven Applications written by Srinivasan Ramalingam 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 2023-12-08 with Computers categories.

Retrieval-Augmented Generation, or RAG, represents a transformative approach in the field of artificial intelligence, merging the capabilities of retrieval systems with generative models to create more informed and contextual responses. At its core, RAG seeks to enhance the output of large language models (LLMs) by supplementing their generative capacities with relevant external data from retrieval systems. This hybrid approach addresses one of the primary limitations of standalone generative models—namely, their reliance on pre-trained knowledge that might not reflect the most current or context-specific information. The architecture of RAG is meticulously designed to dynamically query a database or a search engine, thus enabling the model to ground its responses in the latest or user-specific data, which is particularly crucial for applications requiring up-to-date and precise information, such as financial analytics or personalized healthcare advice. Through the synergistic combination of retrieval and generation, RAG enables systems to bridge the gap between static knowledge embedded within LLMs and the vast, ever-evolving sea of external data, pushing the envelope of what AI-driven applications can achieve (Lewis et al., 2020; Karpukhin et al., 2020; Guu et al., 2020).

Building Generative Ai Applications With Open Source Libraries

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Author : Srikannan Balakrishnan
language : en
Publisher: BPB Publications
Release Date : 2025-03-27

Building Generative Ai Applications With Open Source Libraries written by Srikannan Balakrishnan and has been published by BPB Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-27 with Computers categories.

Generative AI is revolutionizing how we interact with technology, empowering us to create everything from compelling text to intricate code. This book is your practical guide to harnessing the power of open-source libraries, enabling you to build cutting-edge generative AI applications without needing extensive prior experience. In this book, you will journey from foundational concepts like natural language processing and transformers to the practical implementation of large language models. Learn to customize foundational models for specific industries, master text embeddings, and vector databases for efficient information retrieval, and build robust applications using LangChain. Explore open-source models like Llama and Falcon and leverage Hugging Face for seamless implementation. Discover how to deploy scalable AI solutions in the cloud while also understanding crucial aspects of data privacy and ethical AI usage. By the end of this book, you will be equipped with technical skills and practical knowledge, enabling you to confidently develop and deploy your own generative AI applications, leveraging the power of open-source tools to innovate and create. WHAT YOU WILL LEARN ● Building AI applications using LangChain and integrating RAG. ● Implementing large language models like Llama and Falcon. ● Utilizing Hugging Face for efficient model deployment. ● Developing scalable AI applications in cloud environments. ● Addressing ethical considerations and data privacy in AI. ● Practical application of vector databases for information retrieval. WHO THIS BOOK IS FOR This book is for aspiring tech professionals, students, and creative minds seeking to build generative AI applications. While a basic understanding of programming and an interest in AI are beneficial, no prior generative AI expertise is required. TABLE OF CONTENTS 1. Getting Started with Generative AI 2. Overview of Foundational Models 3. Text Processing and Embeddings Fundamentals 4. Understanding Vector Databases 5. Exploring LangChain for Generative AI 6. Implementation of LLMs 7. Implementation Using Hugging Face 8. Developments in Generative AI 9. Deployment of Applications 10. Generative AI for Good

The Generative Ai Practitioner S Guide

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Author : Arup Das
language : en
Publisher: TinyTechMedia LLC
Release Date : 2024-07-20

The Generative Ai Practitioner S Guide written by Arup Das and has been published by TinyTechMedia LLC this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-20 with Computers categories.

Generative AI is revolutionizing the way organizations leverage technology to gain a competitive edge. However, as more companies experiment with and adopt AI systems, it becomes challenging for data and analytics professionals, AI practitioners, executives, technologists, and business leaders to look beyond the buzz and focus on the essential questions: Where should we begin? How do we initiate the process? What potential pitfalls should we be aware of? This TinyTechGuide offers valuable insights and practical recommendations on constructing a business case, calculating ROI, exploring real-life applications, and considering ethical implications. Crucially, it introduces five LLM patterns—author, retriever, extractor, agent, and experimental—to effectively implement GenAI systems within an organization. The Generative AI Practitioner’s Guide: How to Apply LLM Patterns for Enterprise Applications bridges critical knowledge gaps for business leaders and practitioners, equipping them with a comprehensive toolkit to define a business case and successfully deploy GenAI. In today’s rapidly evolving world, staying ahead of the competition requires a deep understanding of these five implementation patterns and the potential benefits and risks associated with GenAI. Designed for business leaders, tech experts, and IT teams, this book provides real-life examples and actionable insights into GenAI’s transformative impact on various industries. Empower your organization with a competitive edge in today’s marketplace using The Generative AI Practitioner’s Guide: How to Apply LLM Patterns for Enterprise Applications. Remember, it’s not the tech that’s tiny, just the book!™

Machine Learning And Generative Ai For Marketing

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Author : Yoon Hyup Hwang
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-08-30

Machine Learning And Generative Ai For Marketing written by Yoon Hyup Hwang 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 2024-08-30 with Computers categories.

Start transforming your data-driven marketing strategies and increasing customer engagement. Learn how to create compelling marketing content using advanced gen AI techniques and stay in touch with the future AI ML landscape. Purchase of the print or Kindle book includes a free eBook in PDF format Key Features Enhance customer engagement and personalization through predictive analytics and advanced segmentation techniques Combine Python programming with the latest advancements in generative AI to create marketing content and address real-world marketing challenges Understand cutting-edge AI concepts and their responsible use in marketing Book Description In the dynamic world of marketing, the integration of artificial intelligence (AI) and machine learning (ML) is no longer just an advantage—it's a necessity. Moreover, the rise of generative AI (GenAI) helps with the creation of highly personalized, engaging content that resonates with the target audience. This book provides a comprehensive toolkit for harnessing the power of GenAI to craft marketing strategies that not only predict customer behaviors but also captivate and convert, leading to improved cost per acquisition, boosted conversion rates, and increased net sales. Starting with the basics of Python for data analysis and progressing to sophisticated ML and GenAI models, this book is your comprehensive guide to understanding and applying AI to enhance marketing strategies. Through engaging content & hands-on examples, you'll learn how to harness the capabilities of AI to unlock deep insights into customer behaviors, craft personalized marketing messages, and drive significant business growth. Additionally, you'll explore the ethical implications of AI, ensuring that your marketing strategies are not only effective but also responsible and compliant with current standards By the conclusion of this book, you'll be equipped to design, launch, and manage marketing campaigns that are not only successful but also cutting-edge. What you will learn Master key marketing KPIs with advanced computational techniques Use explanatory data analysis to drive marketing decisions Leverage ML models to predict customer behaviors, engagement levels, and customer lifetime value Enhance customer segmentation with ML and develop highly personalized marketing campaigns Design and execute effective A/B tests to optimize your marketing decisions Apply natural language processing (NLP) to analyze customer feedback and sentiments Integrate ethical AI practices to maintain privacy in data-driven marketing strategies Who this book is for This book targets a diverse group of professionals: Data scientists and analysts in the marketing domain looking to apply advanced AI ML techniques to solve real-world marketing challenges Machine learning engineers and software developers aiming to build or integrate AI-driven tools and applications for marketing purposes Marketing professionals, business leaders, and entrepreneurs who must understand the impact of AI on marketing Reader are presumed to have a foundational proficiency in Python and a basic to intermediate grasp of ML principles and data science methodologies.