{ "item_title" : "Inside the AI Machine", "item_author" : [" Muni A "], "item_description" : "Inside the AI Machine is your hands-on, plain-English guide to understanding and building real-world AI systems using the latest in large language models (LLMs), agentic frameworks, and tool integrations.Whether you're a developer, student, researcher, or tech enthusiast, this book walks you through how LLMs really work, how they're trained, how they generate responses, and how you can use them to create powerful applications that think, reason, and act. All project code is available on GitHub, with direct links provided in the book. What You'll LearnChapter 1: Under the Hood - The Architecture of Large Language ModelsExplore transformer architectures, embeddings, attention mechanisms, and tokenization-explained clearly with diagrams and analogies. Chapter 2: Training a Giant - Data, Compute, and the Lifecycle of a ModelUnderstand how LLMs are trained: datasets, compute requirements, pretraining vs. fine-tuning, and why alignment is critical. Chapter 3: Fine-Tuning and Prompt-Tuning - Making AI Work for YouDiscover the difference between few-shot prompting, fine-tuning, LoRA, and prompt engineering-and when to use each one. Chapter 4: From Prompt to Response - How AI Decides What to SayBreak down the token-by-token generation process, decoding strategies (greedy, top-k, top-p, beam search), and biases in outputs. Chapter 5: Architecting Agentic Systems with real time projectsDesign blueprints for building agent-based AI using tools like LangChain, AutoGPT, CrewAI, or OpenAI functions + memory chains. Chapter 6: The Toolbelt - Plugging AI into Real-World Tools - with Real Time projectsExplore how agents interact with APIs, browsers, databases, email, files, and even IoT devices through tool integration. Chapter 7: Real-World AI Projects - Case Studies in ActionDive into several case studies: AI customer support agents, automated research assistants, creative AI co-pilots, and business workflow bots. Chapter 8: Multi-Agent Systems - When AIs Collaborate - With Real Time projectsLearn how autonomous agents can coordinate with each other to solve complex problems (e.g., using crew or swarm models). Chapter 9: Building Your First AI Agent - A Hands-On GuideA step-by-step guide using open-source tools (Python + LangChain + OpenAI API or local models) to build a basic autonomous agent. Chapter 10: Guardrails, Ethics, and TrustGo deeper into alignment techniques, AI hallucinations, red-teaming, ethical constraints, and how to make AI safer and more responsible. Chapter 11: Future Frontiers - Where AI Is Heading NextExplore concepts like self-improving agents, lifelong learning, embedded memory, open-ended task planning, and general autonomy. Chapter 12: How to Install Python Chapter 13: Python Basics and Real Time projects", "item_img_path" : "https://covers1.booksamillion.com/covers/bam/9/79/829/785/9798297853256_b.jpg", "price_data" : { "retail_price" : "12.99", "online_price" : "12.99", "our_price" : "12.99", "club_price" : "12.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }

Overview

Customers Also Bought

Details