Must Read LLM Books for AI Pros

Soham Halder

From transformers to prompt engineering, these reads sharpen your edge in the AI race.

Attention Is All You Need: The foundational paper-turned-classic that introduced Transformers and changed NLP forever.

Natural Language Processing with Transformers: A hands-on guide to building, fine-tuning, and deploying transformer-based models in real projects.

Designing Machine Learning Systems: Perfect for AI pros who want to take LLMs from prototypes to scalable, production-ready systems.

Deep Learning by Goodfellow et al: A timeless reference that strengthens the theoretical backbone behind modern LLM architectures.

Generative Deep Learning: Explores how generative models work, a must-read for understanding how LLMs actually create content.

Machine Learning Engineering: Bridges the gap between research and real-world AI deployment, including large models.

Prompt Engineering for LLMs: Focused on mastering prompts, context, and reasoning to unlock maximum performance from LLMs.

AI Engineering: Explains how to integrate LLMs into products, workflows, and enterprise-grade applications.

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