Generative AI with Python and PyTorch, 2nd Edition
Edition: Generative AI with Python and PyTorch is a practical guide to generative models, text generation, and image-generation techniques. Its 450 pages cover LLMs, prompting, RAG, LoRA, GANs, and diffusion, with Python coding and basic math and statistics listed as prerequisites.
At a glance
- Covers LLM concepts and text-generation approaches alongside computer-vision and image-generation topics.
- Topics include prompt engineering, RAG, LangChain, LlamaIndex, PEFT and LoRA, VAEs, GANs, CLIP, and diffusion models.
- The listing says a free PDF eBook comes with purchase of the print or Kindle book.
Reference price: $54.99
Price checked: Nov 14, 2026
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Pros and cons
Pros
- Brings language-model application topics and image-generation methods together in one book.
- Includes both conceptual topics such as transformers and hands-on application themes such as RAG and fine-tuning.
Cons
- The stated prerequisites of Python coding experience and basic math and statistics make this a poor fit for readers seeking a no-prerequisite introduction.
Technical specifications
9 specifications| Edition | 2nd ed. |
|---|---|
| Publisher | Packt Publishing |
| Publication date | March 28, 2025 |
| Language | English |
| Print length | 450 pages |
| ISBN-10 | 1835884458 |
| ISBN-13 | 978-1835884447 |
| Weight listed | 1.71 pounds |
|---|---|
| Dimensions | 7.5 x 1.03 x 9.25 inches |
What to know before buying
- The listing describes both print and Kindle purchase as including a free PDF eBook. Confirm the applicable edition and delivery details for the selected format before purchasing.
Who is it for?
A good fit for
- Data scientists, machine-learning engineers, and software developers with Python experience who want practical exposure to generative AI.
- Readers looking for a single reference spanning LLM tooling and image generation.
Less suited to
- Readers new to Python or without basic math and statistics.
- Buyers seeking a narrow, solely theoretical treatment of one model family.
Customer reviews on Amazon
- 5 stars
59% 59% - 4 stars
14% 14% - 3 stars
19% 19% - 2 stars
0% 0% - 1 star
8% 8%
Aggregate ratings are generally favorable but not unanimous, with a substantial five-star share alongside some three- and one-star ratings. This gives a limited indication of varied reader satisfaction, but does not identify what readers praised or criticized. The listing's stated breadth may suit readers who want both LLM and image-generation topics, while its Python and math prerequisites are relevant to prospective readers.
Frequently asked questions
What does the book cover?
The listing describes LLM foundations, prompt engineering, RAG, fine-tuning with PEFT and LoRA, and image-generation topics including VAEs, GANs, and diffusion models.
Who is the intended reader?
The listing identifies data scientists, machine-learning engineers, and software developers, and says Python coding experience plus basic math and statistics are required.
Does the purchase include a PDF eBook?
The listing claims a free PDF eBook is included with purchase of the print or Kindle book. Check the selected format's listing for the applicable fulfillment details.
How long is the print book?
The listed print length is 450 pages.
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