Mastering Agentic Llm

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Mastering Agentic Llm

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Author : Ronald Taylor
language : en
Publisher: Independently Published
Release Date : 2025-03-09

Mastering Agentic Llm 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 2025-03-09 with Computers categories.

Mastering Agentic LLM: A Step-by-Step Practical Blueprint to Building Self-Directed AI Systems That Act Independently and Solve Your Digital Challenges is your definitive guide to the next generation of intelligent automation. This book demystifies Agentic AI-from cutting-edge RAG systems and cognitive frameworks to practical implementations using Python and large language models-by offering a comprehensive, hands-on approach to designing self-directed AI workflows and intelligent systems for real-world applications. Drawing on the latest research and practical insights, this guide covers everything from the fundamentals of natural language processing to advanced techniques in multi-agent systems and autonomous AI. You'll discover how to build agentic workflows, master modern agentic architectures, and harness the power of foundation models to revolutionize project management and intelligent automation. With detailed step-by-step instructions, this practical guide empowers you to innovate with AI, design machine learning systems that are production-ready, and develop iterative processes that make your applications future-proof. Whether you're an AI engineer looking to build wealth through cutting-edge technology, a business leader seeking to streamline operations with intelligent automation workflows, or a tech enthusiast eager to explore the frontier of agentic AI systems, this book offers the tools, techniques, and insights you need to succeed in today's competitive digital landscape. Take action now and join the AI revolution-unlock your potential to build autonomous, self-directed systems that not only think but also act independently. Elevate your skills, drive innovation, and become a leader in the new era of Agentic AI. Order your copy today and start building the future of intelligent automation!

Mastering Nlp From Foundations To Llms

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Author : Lior Gazit
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-04-26

Mastering Nlp From Foundations To Llms written by Lior Gazit 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 2024-04-26 with Computers categories.

Enhance your NLP proficiency with modern frameworks like LangChain, explore mathematical foundations and code samples, and gain expert insights into current and future trends Key Features Learn how to build Python-driven solutions with a focus on NLP, LLMs, RAGs, and GPT Master embedding techniques and machine learning principles for real-world applications Understand the mathematical foundations of NLP and deep learning designs Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionDo you want to master Natural Language Processing (NLP) but don’t know where to begin? This book will give you the right head start. Written by leaders in machine learning and NLP, Mastering NLP from Foundations to LLMs provides an in-depth introduction to techniques. Starting with the mathematical foundations of machine learning (ML), you’ll gradually progress to advanced NLP applications such as large language models (LLMs) and AI applications. You’ll get to grips with linear algebra, optimization, probability, and statistics, which are essential for understanding and implementing machine learning and NLP algorithms. You’ll also explore general machine learning techniques and find out how they relate to NLP. Next, you’ll learn how to preprocess text data, explore methods for cleaning and preparing text for analysis, and understand how to do text classification. You’ll get all of this and more along with complete Python code samples. By the end of the book, the advanced topics of LLMs’ theory, design, and applications will be discussed along with the future trends in NLP, which will feature expert opinions. You’ll also get to strengthen your practical skills by working on sample real-world NLP business problems and solutions.What you will learn Master the mathematical foundations of machine learning and NLP Implement advanced techniques for preprocessing text data and analysis Design ML-NLP systems in Python Model and classify text using traditional machine learning and deep learning methods Understand the theory and design of LLMs and their implementation for various applications in AI Explore NLP insights, trends, and expert opinions on its future direction and potential Who this book is for This book is for deep learning and machine learning researchers, NLP practitioners, ML/NLP educators, and STEM students. Professionals working with text data as part of their projects will also find plenty of useful information in this book. Beginner-level familiarity with machine learning and a basic working knowledge of Python will help you get the best out of this book.

Mastering Openai For Enterprise

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Author : Sriram Subramanian
language : en
Publisher: Orange Education Pvt Ltd
Release Date : 2025-03-11

Mastering Openai For Enterprise written by Sriram Subramanian and has been published by Orange Education Pvt Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-11 with Computers categories.

TAGLINE Master OpenAI and Unlock the Future of AI-Powered Innovation KEY FEATURES ● In-depth exploration of OpenAI tools, models, and enterprise use cases ● Hands-on projects with extensive code samples for practical learning ● Real-world case studies with ethical AI insights and best practices DESCRIPTION OpenAI is transforming industries with cutting-edge AI models, redefining how businesses operate, innovate, and compete. Mastering OpenAI for Enterprise is your definitive guide to harnessing the power of OpenAI’s groundbreaking technologies, including GPT models, DALL·E, and more. Designed for AI engineers, developers, and business leaders, this book offers an in-depth understanding of OpenAI’s tools and their real-world applications in enterprise settings. This hands-on guide provides a structured learning path, featuring practical code samples, step-by-step implementations, and industry case studies that bridge theory with practice. Whether you're building intelligent chatbots, leveraging AI for automation, or exploring generative AI for creative solutions, this book equips you with the knowledge and skills to seamlessly integrate OpenAI into your workflows. Ethical AI development and responsible implementation are also key themes, ensuring that innovation is balanced with accountability. As AI continues to evolve at an unprecedented pace, mastering OpenAI is no longer optional—it’s essential. The future belongs to those who can effectively leverage these technologies. Don’t get left behind—equip yourself with the expertise needed to stay ahead in the AI revolution. WHAT WILL YOU LEARN ● Gain expertise in OpenAI’s models, APIs, and enterprise applications ● Build intelligent chatbots and virtual assistants using ChatGPT ● Implement ethical AI practices for responsible and fair deployment ● Optimize and deploy OpenAI models for scalable business solutions ● Analyze real-world case studies to drive AI-powered innovation ● Leverage generative AI to automate, enhance, and transform workflows WHO IS THIS BOOK FOR? This book is tailored for both beginners and experienced professionals looking to harness the power of OpenAI. Ideal for application architects, developers, AI engineers, CTOs, and technology leaders, it provides the essential knowledge and hands-on skills needed to integrate OpenAI solutions into enterprise applications effectively. TABLE OF CONTENTS 1. OpenAI Primer 2. Deep Learning, Transformers, and OpenAI Tools 3. Natural Language Processing with GPTs 4. Computer Vision with DALL-E and CLIP 5. Building Chatbots with ChatGPT 6. AI Ethics and Responsible AI 7. Deploying OpenAI Models 8. Case Studies and Best Practices Appendix. Retrieval-Augmented Generation (RAG) Index

Agentic Ai A Practical Guide To Build Agent Based Ai Systems That Think And Act

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Author : Tejas Patthi
language : en
Publisher: Tejas Patthi
Release Date : 2025-06-30

Agentic Ai A Practical Guide To Build Agent Based Ai Systems That Think And Act written by Tejas Patthi and has been published by Tejas Patthi this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-30 with Computers categories.

Build real-world AI systems that do more than just respond. They think, plan, and act with purpose. Agentic AI is a comprehensive, hands-on guide to building autonomous AI agents using Python, large language models (LLMs), LangGraph, CrewAI, FAISS, and other modern tools. Whether you are an AI developer, a machine learning engineer, or a tech enthusiast, this book will help you move beyond simple chatbots and prompt-based models into the advanced world of intelligent, agent-based systems that function independently and handle real tasks. In this step-by-step guide, you’ll learn how to build LLM-powered autonomous agents capable of reasoning, tool use, memory recall, and multi-step task execution. From integrating with real-world APIs to deploying production-ready agent workflows, you'll gain the skills to create powerful and reliable agentic AI systems using today's top frameworks and best practices. 🔍 What You Will Learn: How to build autonomous AI agents that work independently without constant human input How to create agents with long-term memory using vector databases like FAISS and Chroma How to orchestrate multi-agent systems using frameworks like LangGraph and CrewAI How to integrate AI with external tools, APIs, and web services How to use Python to script smart agent behaviors and decision-making logic How to deploy agentic systems in cloud environments or containers with live monitoring How to implement agent safety, performance testing, and real-time feedback loops 💡 Why This Book Is Different: This is not just another theoretical AI book. Agentic AI is a project-based, code-driven manual that gives you everything you need to: Build tool-using AI assistants, copilots, and multi-agent task managers Use LangChain, LangGraph, CrewAI, and LLM toolchains effectively Combine LLMs with real-time data, plugins, memory, and feedback systems Design and deploy goal-driven AI agents with full autonomy and context awareness Stay ahead in the fast-evolving field of agent-based AI and LLM integration 🧠 Tools and Technologies Covered: Python 3.x LangGraph & LangChain CrewAI & OpenAgents ChromaDB & FAISS for memory OpenAI, Claude, Gemini, HuggingFace APIs FastAPI, Docker, REST APIs, and Webhooks Autonomous task chaining, multi-agent routing, and smart tool use 📦 Who Should Read This Book? AI Engineers ready to move beyond static models Python Developers exploring LLMs and autonomous systems Tech founders building smart assistants and AI copilots Data Scientists interested in real-world AI deployment Prompt engineers ready to level up into full-stack AI workflows

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.

Designing Agentic Ai Architecture And Development Strategies

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Author : Anand Vemula
language : en
Publisher: Anand Vemula
Release Date :

Designing Agentic Ai Architecture And Development Strategies 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.

Designing Agentic AI: Architecture and Development Strategies offers a groundbreaking blueprint for creating AI agents that move beyond simple automation into the realm of persistent, autonomous, and goal-directed intelligence. This book unpacks the essential layers and architectural foundations that enable modern AI systems to plan, reason, act, adapt, and self-correct in complex real-world environments. Across five comprehensive parts, the book explores the evolution of agentic systems, from early automation tools to dynamic agents capable of long-term memory, adaptive reasoning, and creative problem-solving. It introduces core concepts such as cognitive loops, multimodal perception-action systems, planner-executor architectures, memory persistence, and self-debugging capabilities. Developers are guided through the use of leading frameworks like LangChain, AutoGPT, and CrewAI, while also learning when to build custom solutions versus integrating existing components. Advanced topics such as multi-agent collaboration, meta-reasoning, ethical guardrails, tool use, and system auditability are thoroughly examined. The book culminates with a future-facing exploration of self-upgrading agents, edge deployments, and the path toward Artificial General Agents (AGAs). It bridges technical execution with regulatory and ethical foresight, ensuring responsible innovation. Written for AI architects, system designers, researchers, and forward-thinking technologists, Designing Agentic AI is a definitive resource for anyone aiming to build intelligent systems that think, plan, and act with purpose—bringing the next generation of AI from concept to code.

Generative Deep Learning

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Author : David Foster
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2019-06-28

Generative Deep Learning written by David Foster and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-06-28 with Computers categories.

Generative modeling is one of the hottest topics in AI. It’s now possible to teach a machine to excel at human endeavors such as painting, writing, and composing music. With this practical book, machine-learning engineers and data scientists will discover how to re-create some of the most impressive examples of generative deep learning models, such as variational autoencoders,generative adversarial networks (GANs), encoder-decoder models and world models. Author David Foster demonstrates the inner workings of each technique, starting with the basics of deep learning before advancing to some of the most cutting-edge algorithms in the field. Through tips and tricks, you’ll understand how to make your models learn more efficiently and become more creative. Discover how variational autoencoders can change facial expressions in photos Build practical GAN examples from scratch, including CycleGAN for style transfer and MuseGAN for music generation Create recurrent generative models for text generation and learn how to improve the models using attention Understand how generative models can help agents to accomplish tasks within a reinforcement learning setting Explore the architecture of the Transformer (BERT, GPT-2) and image generation models such as ProGAN and StyleGAN

Kimi K2 Unlocked

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Author : Guillaume Lessard
language : en
Publisher: iD01t Productions
Release Date : 2025-07-22

Kimi K2 Unlocked written by Guillaume Lessard and has been published by iD01t Productions this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-22 with Computers categories.

This is not just another AI book. This is your key to real execution. Kimi K2 Unlocked is the ultimate hands-on guide for developers, coders, and innovators who want to build, automate, and deploy powerful AI workflows using the open agent Kimi K2. Whether you're launching from a local machine, integrating Claude-grade intelligence, or building end-to-end automation pipelines, this book gives you everything you need to get started fast and scale with confidence. You’ll learn how to: ✅ Install Kimi K2 locally using vLLM, Hugging Face, or SGLang ✅ Launch real commands that code, fix bugs, write reports, and automate tasks ✅ Deploy agentic workflows using prompt chaining, file memory, and self-repair ✅ Optimize for Groq, Claude, and open-source LLMs with direct terminal execution ✅ Use Kimi K2 across Python, HTML, CLI, and real-world projects ✅ Monetize your knowledge with included CTA templates and freelance-ready tools Included in this package: A full quick-start deployment guide A complete Claude-style prompt pack Use-case examples across dev stacks Professional Markdown and PDF layout Designed for freelance work, dev tools, and product launches This book turns Kimi K2 into your personal AI operator. It works. It writes. It executes. It builds. Kimi K2 Unlocked is for real builders. No fluff. No theory. Just the fastest way to get agentic AI working for you.

Data Science For Marketing Analytics

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Author : Mirza Rahim Baig
language : en
Publisher: Packt Publishing Ltd
Release Date : 2021-09-07

Data Science For Marketing Analytics written by Mirza Rahim Baig 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 2021-09-07 with Computers categories.

Turbocharge your marketing plans by making the leap from simple descriptive statistics in Excel to sophisticated predictive analytics with the Python programming language Key FeaturesUse data analytics and machine learning in a sales and marketing contextGain insights from data to make better business decisionsBuild your experience and confidence with realistic hands-on practiceBook Description Unleash the power of data to reach your marketing goals with this practical guide to data science for business. This book will help you get started on your journey to becoming a master of marketing analytics with Python. You'll work with relevant datasets and build your practical skills by tackling engaging exercises and activities that simulate real-world market analysis projects. You'll learn to think like a data scientist, build your problem-solving skills, and discover how to look at data in new ways to deliver business insights and make intelligent data-driven decisions. As well as learning how to clean, explore, and visualize data, you'll implement machine learning algorithms and build models to make predictions. As you work through the book, you'll use Python tools to analyze sales, visualize advertising data, predict revenue, address customer churn, and implement customer segmentation to understand behavior. By the end of this book, you'll have the knowledge, skills, and confidence to implement data science and machine learning techniques to better understand your marketing data and improve your decision-making. What you will learnLoad, clean, and explore sales and marketing data using pandasForm and test hypotheses using real data sets and analytics toolsVisualize patterns in customer behavior using MatplotlibUse advanced machine learning models like random forest and SVMUse various unsupervised learning algorithms for customer segmentationUse supervised learning techniques for sales predictionEvaluate and compare different models to get the best outcomesOptimize models with hyperparameter tuning and SMOTEWho this book is for This marketing book is for anyone who wants to learn how to use Python for cutting-edge marketing analytics. Whether you're a developer who wants to move into marketing, or a marketing analyst who wants to learn more sophisticated tools and techniques, this book will get you on the right path. Basic prior knowledge of Python and experience working with data will help you access this book more easily.

Ai Agents In Action

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Author : Micheal Lanham
language : en
Publisher: Simon and Schuster
Release Date : 2025-03-04

Ai Agents In Action written by Micheal Lanham 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 2025-03-04 with Computers categories.

Create LLM-powered autonomous agents and intelligent assistants tailored to your business and personal needs. From script-free customer service chatbots to fully independent agents operating seamlessly in the background, AI-powered assistants represent a breakthrough in machine intelligence. In AI Agents in Action, you'll master a proven framework for developing practical agents that handle real-world business and personal tasks. Author Micheal Lanham combines cutting-edge academic research with hands-on experience to help you: • Understand and implement AI agent behavior patterns • Design and deploy production-ready intelligent agents • Leverage the OpenAI Assistants API and complementary tools • Implement robust knowledge management and memory systems • Create self-improving agents with feedback loops • Orchestrate collaborative multi-agent systems • Enhance agents with speech and vision capabilities You won't find toy examples or fragile assistants that require constant supervision. AI Agents in Action teaches you to build trustworthy AI capable of handling high-stakes negotiations. You'll master prompt engineering to create agents with distinct personas and profiles, and develop multi-agent collaborations that thrive in unpredictable environments. Beyond just learning a new technology, you'll discover a transformative approach to problem-solving. About the technology Most production AI systems require many orchestrated interactions between the user, AI models, and a wide variety of data sources. AI agents capture and organize these interactions into autonomous components that can process information, make decisions, and learn from interactions behind the scenes. This book will show you how to create AI agents and connect them together into powerful multi-agent systems. About the book In AI Agents in Action, you’ll learn how to build production-ready assistants, multi-agent systems, and behavioral agents. You’ll master the essential parts of an agent, including retrieval-augmented knowledge and memory, while you create multi-agent applications that can use software tools, plan tasks autonomously, and learn from experience. As you explore the many interesting examples, you’ll work with state-of-the-art tools like OpenAI Assistants API, GPT Nexus, LangChain, Prompt Flow, AutoGen, and CrewAI. What's inside • Knowledge management and memory systems • Feedback loops for continuous agent learning • Collaborative multi-agent systems • Speech and computer vision About the reader For intermediate Python programmers. About the author Micheal Lanham is a software and technology innovator with over 20 years of industry experience. He has authored books on deep learning, including Manning’s Evolutionary Deep Learning. Table of Contents 1 Introduction to agents and their world 2 Harnessing the power of large language models 3 Engaging GPT assistants 4 Exploring multi-agent systems 5 Empowering agents with actions 6 Building autonomous assistants 7 Assembling and using an agent platform 8 Understanding agent memory and knowledge 9 Mastering agent prompts with prompt flow 10 Agent reasoning and evaluation 11 Agent planning and feedback A Accessing OpenAI large language models B Python development environment