BUILDING A COMPREHENSIVE AI MODEL: Large Language Models, Generative AI, DeepSeek, Ethics & Accountability

by Marc Stanford

What if you could turn raw data into powerful, responsible intelligence without a PhD in computer science?

Building a Comprehensive AI Model is your roadmap to designing, training, fine-tuning, and deploying cutting-edge AI systems. From your very first classifier to state-of-the-art Large Language Models and Generative AI with a peek at DeepSeek. Marc Stanford demystifies the entire workflow, enabling you to create technology that ethically transforms industries.

Inside, you'll
• Collecting & cleaning data like a pro; no more 'garbage in, garbage out.'
• Choosing the right algorithms for vision, NLP, finance, retail, and healthcare.
• Training, hyperparameter tuning, and model‑evaluation secrets that boost accuracy.
• Building production‑grade LLMs, chatbots, and creative generative models.
• Governance, bias mitigation, and regulatory compliance to ensure your AI remains accountable.

Whether you're a curious beginner, a Python‑savvy developer, or a business leader seeking an edge, this book delivers battle‑tested frameworks, code samples, and real‑world case studies you can apply today.

Stop just using AI tools, start building them. Pick up your copy and ship your first comprehensive AI model this week!

338 pages, Kindle Edition

Published January 31, 2025

Reviews

[Rodrigo · Rating 5 out of 5]

Great resource for beginners

This is a helpful resource for anyone interested in AI, large language models, and generative AI. It explains complex concepts in a simple way, making it great for beginners and professionals. I especially liked the sections on AI ethics and applications in healthcare, finance, and content creation. It’s definitely a solid guide for anyone starting. It may not be deep enough if you already know AI a bit.

[Conan Taggert · Rating 5 out of 5]

Finally, a book that contains all the information needed to understand and connect loose ends in the age of AI. The author accomplished the remarkable goal of breaking down the highly complicated details of large language models, neural networks, and generative AI in small portions, thus making them available for non-computer scientists to digest and understand.

[Önen Togar · Rating 5 out of 5]

I've worked with AI on a user level for a few years. I've made some modest progress in writing effective prompts and getting results such as text, images, and video. However, after reading Marc Stanford's well-structured and explained book, I feel ready to start building my first AI model custom-tailored for my exact needs. I highly recommend this book since it covers the areas of LLM and generative AI in great detail and emphasizes ethics, bias mitigation, and accountability.