Building Llm Applications With Python A Practical Guide
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Building Llm Applications With Python
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Author : ANAND. VEMULA
language : en
Publisher:
Release Date : 2024
Building Llm Applications With Python written by ANAND. VEMULA and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024 with categories.
Building Large Language Model Llm Applications
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Author : Anand Vemula
language : en
Publisher: Anand Vemula
Release Date :
Building Large Language Model Llm 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.
"Building LLM Apps" is a comprehensive guide that equips readers with the knowledge and practical skills needed to develop applications utilizing large language models (LLMs). The book covers various aspects of LLM application development, starting from understanding the fundamentals of LLMs to deploying scalable and efficient solutions. Beginning with an introduction to LLMs and their importance in modern applications, the book explores the history, key concepts, and popular architectures like GPT and BERT. Readers learn how to set up their development environment, including hardware and software requirements, installing necessary tools and libraries, and leveraging cloud services for efficient development and deployment. Data preparation is essential for training LLMs, and the book provides insights into gathering and cleaning data, annotating and labeling data, and handling imbalanced data to ensure high-quality training datasets. Training large language models involves understanding training basics, best practices, distributed training techniques, and fine-tuning pre-trained models for specific tasks. Developing LLM applications requires designing user interfaces, integrating LLMs into existing systems, and building interactive features such as chatbots, text generation, sentiment analysis, named entity recognition, and machine translation. Advanced LLM techniques like prompt engineering, transfer learning, multi-task learning, and zero-shot learning are explored to enhance model capabilities. Deployment and scalability strategies are discussed to ensure smooth deployment of LLM applications while managing costs effectively. Security and ethics in LLM apps are addressed, covering bias detection, fairness, privacy, security, and ethical considerations to build responsible AI solutions. Real-world case studies illustrate the practical applications of LLMs in various domains, including customer service, healthcare, and finance. Troubleshooting and optimization techniques help readers address common issues and optimize model performance. Looking towards the future, the book highlights emerging trends and developments in LLM technology, emphasizing the importance of staying updated with advancements and adhering to ethical AI practices. "Building LLM Apps" serves as a comprehensive resource for developers, data scientists, and business professionals seeking to harness the power of large language models in their applications.
Building Data Driven Applications With Llamaindex
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Author : Andrei Gheorghiu
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-05-10
Building Data Driven Applications With Llamaindex written by Andrei Gheorghiu 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 2024-05-10 with Computers categories.
Solve real-world problems easily with artificial intelligence (AI) using the LlamaIndex data framework to enhance your LLM-based Python applications Key Features Examine text chunking effects on RAG workflows and understand security in RAG app development Discover chatbots and agents and learn how to build complex conversation engines Build as you learn by applying the knowledge you gain to a hands-on project Book DescriptionDiscover the immense potential of Generative AI and Large Language Models (LLMs) with this comprehensive guide. Learn to overcome LLM limitations, such as contextual memory constraints, prompt size issues, real-time data gaps, and occasional ‘hallucinations’. Follow practical examples to personalize and launch your LlamaIndex projects, mastering skills in ingesting, indexing, querying, and connecting dynamic knowledge bases. From fundamental LLM concepts to LlamaIndex deployment and customization, this book provides a holistic grasp of LlamaIndex's capabilities and applications. By the end, you'll be able to resolve LLM challenges and build interactive AI-driven applications using best practices in prompt engineering and troubleshooting Generative AI projects.What you will learn Understand the LlamaIndex ecosystem and common use cases Master techniques to ingest and parse data from various sources into LlamaIndex Discover how to create optimized indexes tailored to your use cases Understand how to query LlamaIndex effectively and interpret responses Build an end-to-end interactive web application with LlamaIndex, Python, and Streamlit Customize a LlamaIndex configuration based on your project needs Predict costs and deal with potential privacy issues Deploy LlamaIndex applications that others can use Who this book is for This book is for Python developers with basic knowledge of natural language processing (NLP) and LLMs looking to build interactive LLM applications. Experienced developers and conversational AI developers will also benefit from the advanced techniques covered in the book to fully unleash the capabilities of the framework.
Build Ai Agents With Langchain Langgraph
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Author : Jude Max
language : en
Publisher: Independently Published
Release Date : 2025-06-19
Build Ai Agents With Langchain Langgraph written by Jude Max and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-19 with Computers categories.
Unlock the true potential of Generative AI and transform your Python development skills! This definitive guide empowers you to move beyond basic LLM prompts and build intelligent, autonomous AI Agents that think, act, and solve complex problems. "Build AI Agents with LangChain & LangGraph" is your hands-on roadmap to mastering the cutting-edge frameworks that power the next generation of AI applications. Discover how to create dynamic LLM workflows capable of tool use, memory, and self-correction. Who This Book Is For: Python Developers eager to integrate advanced Large Language Models into their projects. Machine Learning Engineers seeking practical strategies for AI agent orchestration. Anyone ready to build production-ready, intelligent chatbots and automated systems. What You'll Learn & Build: Master LangChain & LangGraph Fundamentals: Design robust LLM workflows with nodes, edges, and state management. Integrate Powerful Tools: Enable your AI agents to interact with external APIs, perform web browsing, and execute code. Build Real-World AI Applications: Dive into practical case studies, including an Autonomous Research Agent and a Smart Customer Support Co-pilot. Navigate Ethical AI: Implement crucial safeguards for ethical AI, privacy, security, and human oversight. Deploy with Confidence: Learn full-stack integration, API exposure, and debugging techniques for seamless deployment. Optimize for Performance: Strategies for efficient AI development and cost-effective LLM workflows. Stop just talking to AI. Start building with it. Your journey to creating powerful, intelligent AI agents begins here!
The Practical Guide To Large Language Models
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Author : Ivan Gridin
language : en
Publisher: Apress
Release Date : 2025-12-13
The Practical Guide To Large Language Models written by Ivan Gridin and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-12-13 with Computers categories.
This book is a practical guide to harnessing Hugging Face's powerful transformers library, unlocking access to the largest open-source LLMs. By simplifying complex NLP concepts and emphasizing practical application, it empowers data scientists, machine learning engineers, and NLP practitioners to build robust solutions without delving into theoretical complexities. The book is structured into three parts to facilitate a step-by-step learning journey. Part One covers building production-ready LLM solutions introduces the Hugging Face library and equips readers to solve most of the common NLP challenges without requiring deep knowledge of transformer internals. Part Two focuses on empowering LLMs with RAG and intelligent agents exploring Retrieval-Augmented Generation (RAG) models, demonstrating how to enhance answer quality and develop intelligent agents. Part Three covers LLM advances focusing on expert topics such as model training, principles of transformer architecture and other cutting-edge techniques related to the practical application of language models. Each chapter includes practical examples, code snippets, and hands-on projects to ensure applicability to real-world scenarios. This book bridges the gap between theory and practice, providing professionals with the tools and insights to develop practical and efficient LLM solutions. What you will learn: What are the different types of tasks modern LLMs can solve How to select the most suitable pre-trained LLM for specific tasks How to enrich LLM with a custom knowledge base and build intelligent systems What are the core principles of Language Models, and how to tune them How to build robust LLM-based AI Applications Who this book is for: Data scientists, machine learning engineers, and NLP specialists with basic Python skills, introductory PyTorch knowledge, and a primary understanding of deep learning concepts, ready to start applying Large Language Models in practice.
Generative Ai And Rag For Beginners
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Author : Oscar Mazzanti
language : en
Publisher: Emmanuel Livingstone
Release Date : 2025-12-17
Generative Ai And Rag For Beginners written by Oscar Mazzanti and has been published by Emmanuel Livingstone this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-12-17 with Computers categories.
Unlock the Power of Generative AI with this Step-by-Step Guide! Are you ready to dive into the world of Artificial Intelligence and build your own intelligent applications? Generative AI and RAG for Beginners is the perfect starting point for anyone eager to explore how large language models (LLMs) and Retrieval-Augmented Generation (RAG) work in the real world. This practical, hands-on guide will walk you through the process of creating your very own AI-powered solutions using LangChain and Python. Whether you're a complete beginner or looking to enhance your existing knowledge, this book breaks down complex concepts into simple, actionable steps. You’ll learn how to: Build powerful AI applications that retrieve accurate information and generate contextually aware responses. Master LangChain and Python to create efficient workflows, connect databases, and integrate external data sources. Understand RAG systems and how they enhance the capabilities of traditional language models by incorporating real-world knowledge. Navigate real-world challenges with expert tips on improving performance, optimizing retrieval pipelines, and handling large datasets. Create practical AI solutions for industries like business, education, research, and more! Packed with clear explanations, code examples, and project-based learning, this guide will help you develop a strong foundation in AI development and prepare you for future challenges in machine learning and natural language processing. What You'll Gain: Hands-on experience with building and deploying AI models. Clear guidance on leveraging LangChain for LLM-powered applications. Practical knowledge of RAG and its real-world applications. Proven tips for tackling common issues and improving model performance. Whether you're creating AI assistants, building data-driven applications, or exploring new ways to interact with data, this book gives you the tools to succeed. Get ready to bring your AI ideas to life—no prior experience required! Start building the future of AI today. Grab your copy of Generative AI and RAG for Beginners and take your first step toward becoming a skilled AI engineer!
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 Free with your book: PDF Copy, AI Assistant, and Next-Gen Reader 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 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.
Unveiling Langchain And Llm For Python Developers
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Author : Matthew D Passmore
language : en
Publisher: Independently Published
Release Date : 2024-07-09
Unveiling Langchain And Llm For Python Developers written by Matthew D Passmore and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-09 with Computers categories.
Unlock the power of Language Models and revolutionize your web development skills with "Unveiling LangChain and LLM for Python Developers: Your Beginner-Friendly Guide to Building Intelligent, Scalable, and Unique Web Applications (LLMs Decoded with TensorFlow, Hugging Face, and More)." In this comprehensive guide, dive into the world of Large Language Models (LLMs) and learn how to leverage their capabilities to create cutting-edge web applications. Whether you're a seasoned developer or just starting your journey, this book offers a clear and practical approach to mastering LLMs using popular frameworks like TensorFlow and Hugging Face. **What You'll Discover: ** - **Foundations of LLMs**: Understand the basics of language models, their architectures, and how they process and generate human-like text. - **Hands-On Tutorials**: Step-by-step instructions to integrate LLMs into your Python projects, complete with code examples and detailed explanations. - **Scalable Solutions**: Learn how to build applications that can handle large-scale data and deliver real-time performance. - **Advanced Techniques**: Explore sophisticated topics such as fine-tuning pre-trained models, optimizing performance, and deploying LLMs in production environments. - **Practical Applications**: Real-world case studies demonstrating how LLMs can be used in chatbots, content generation, sentiment analysis, and more. With a focus on practical knowledge and real-world applications, this book equips you with the skills to create intelligent, scalable, and unique web applications that stand out in today's competitive landscape. Whether you're aiming to enhance user experience, automate content creation, or simply explore the potential of artificial intelligence in web development, "Unveiling LangChain and LLM for Python Developers" is your essential guide to the future of web development
Mastering Ai With Confidence
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Author : Ronald Taylor
language : en
Publisher: Independently Published
Release Date : 2025-01-14
Mastering Ai With Confidence written by Ronald Taylor and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-14 with Computers categories.
"Mastering AI with Confidence: The Definitive Guide to NLP and LLM Applications" Unlock the secrets of Natural Language Processing (NLP) and Large Language Models (LLMs) in this all-encompassing guide designed for developers, researchers, and enthusiasts. Whether you're a beginner exploring NLP with Python, an advanced user diving into transformer architectures, or an innovator ready to build cutting-edge AI-powered applications, this book has everything you need to master modern NLP technologies. With practical insights and step-by-step projects, this book bridges theory and hands-on practice. Learn to: Develop practical NLP pipelines using Python and frameworks like LangChain and LlamaIndex. Build and fine-tune your own Large Language Models (LLMs) from scratch. Explore transformer models like GPT, BERT, and T5 and integrate them into real-world applications. Create multi-agent AI systems that use tools like LangGraph and CrewAI to enhance collaboration and automation. Implement Retrieval-Augmented Generation (RAG) systems for accurate, context-aware outputs. From foundational concepts for beginners to advanced topics in computational linguistics and LLM prompt programming, this book is your comprehensive companion. You'll delve into the future of AI with chapters on generative AI trends, LLM application development, and emerging tools like LangGraph AI Agents. Ideal for those exploring multi-agent systems, LLM programming, and practical applications of AI, this book is designed to meet the needs of developers at every skill level. Whether you're building tools for Rust-based NLP projects, exploring LLM-powered chatbots, or diving into deep learning for NLP, this resource is your ultimate guide to success. Packed with real-world examples, code illustrations, and engaging projects, this book ensures you're not just learning but mastering NLP and LLMs with confidence. Perfect for: AI enthusiasts seeking practical skills. Developers building advanced LLM applications. Professionals using tools like LangChain, LlamaIndex, and CrewAI. Take your place at the forefront of AI innovation with "Mastering AI with Confidence." Get your copy today and turn cutting-edge NLP technologies into groundbreaking solutions.
Machine Learning With Python Programming
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Author : Richard D Crowley
language : en
Publisher: Independently Published
Release Date : 2025-02-25
Machine Learning With Python Programming written by Richard D Crowley and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-25 with Computers categories.
This book provides a structured and accessible pathway into the world of machine learning.1 Beginning with fundamental concepts and progressing through advanced topics, it covers essential Python libraries, mathematical foundations, and practical applications. The book delves into supervised and unsupervised learning, natural language processing, computer vision, time series analysis, and recommender systems.2 It also addresses critical aspects of model deployment, ethical considerations, and future trends, including reinforcement learning, GANs, and AutoML. With practical examples, troubleshooting tips, and a glossary, this resource empowers readers to build and deploy effective machine learning models while understanding the broader implications of AI.