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Just finished "101 Generative AI Projects: Diffusion Models, Transformers, ChatGPT, and Other LLMs " - my thoughts
The 101 Generative AI Projects: Diffusion Models, Transformers, ChatGPT, and Other LLMs book provides comprehensive coverage of transformers that I haven't found in any other resource.
Best practices for AI projects?
I'm working on a project that involves Diffusion models and looking for advice on best practices. Has anyone read "101 Generative AI Projects: Diffusion Models, Transformers, ChatGPT, and Other LLMs " and can recommend specific chapters?
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Just finished "101 Generative AI Projects: Diffusion Models, Transformers, ChatGPT, and Other LLMs " - my thoughts
What sets 101 Generative AI Projects: Diffusion Models, Transformers, ChatGPT, and Other LLMs apart is its focus on practical Generative AI techniques. You can immediately apply what you learn to real projects.
How does "101 Generative AI Projects: Diffusion Models, Transformers, ChatGPT, and Other LLMs " compare to other resources?
I'm considering getting "101 Generative AI Projects: Diffusion Models, Transformers, ChatGPT, and Other LLMs " but wanted to hear from those who have read it. How does it compare to other books or online courses on transformers?
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The code samples in 101 Generative AI Projects: Diffusion Models, Transformers, ChatGPT, and Other LLMs (Paperback) are well-documented and easy to follow.
I've been recommending 101 Generative AI Projects: Diffusion Models, Transformers, ChatGPT, and Other LLMs (Paperback) to all my coding bootcamp students.
I've been using the techniques from 101 Generative AI Projects: Diffusion Models, Transformers, ChatGPT, and Other LLMs (Paperback) in my current project with great success.
Has anyone tried the exercises in chapter 7? They're challenging but rewarding!
I'm halfway through 101 Generative AI Projects: Diffusion Models, Transformers, ChatGPT, and Other LLMs (Paperback) and already seeing improvements in my code.