Overview

Unlock the full potential of Large Language Models (LLMs) with this definitive, hands-on masterpiece penned by AI authority Silver Hawk. Whether you are a developer, data scientist, business leader, or AI enthusiast, Mastering Large Language Models from Scratch delivers everything you need to build, train, fine-tune, and deploy production-ready LLMs using Python, PyTorch, Retrieval-Augmented Generation (RAG), and Reinforcement Learning from Human Feedback (RLHF). Spanning 15 meticulously structured chapters, this comprehensive guide takes you from the mathematical foundations of Transformers and tokenization to cutting-edge topics like multimodal models, GPT-4 architecture insights, LoRA/QLoRA efficiency, bias mitigation, toxicity detection, and enterprise-grade deployment on cloud platforms. Discover how LLMs are revolutionizing healthcare diagnostics, financial forecasting, legal document automation, customer service chatbots, content generation, and workflow optimization. Rich with ready-to-run code, real-world case studies, performance benchmarks, and ethical frameworks, this book equips you to create custom LLMs that outperform proprietary models while minimizing costs and environmental impact. Stay ahead of the AI revolution-master prompt engineering, instruction tuning, parameter-efficient fine-tuning, vector databases, and the latest 2025 trends in open-source LLMs. Keywords: Large Language Models, LLMs from scratch, Python LLM tutorial, PyTorch deep learning, Retrieval-Augmented Generation, RAG implementation, Reinforcement Learning RLHF, Transformer architecture, BERT GPT training, fine-tuning LLMs, LoRA QLoRA, multimodal AI, ethical AI, bias mitigation, LLM deployment, AI automation, healthcare AI, finance AI, legal tech, customer service automation, GPT-4 insights, open-source LLMs.

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