101 Generative AI Projects: Diffusion Models, Transformers, ChatGPT, and Other LLMs (Paperback)
If you want practical clarity, this is a strong pick: Generative AI, Diffusion models, ChatGPT, transformers presented in a way that turns into decisions, not just notes.
ISBN: 9798291798089 Published: July 10, 2025 Generative AI, Diffusion models, ChatGPT, transformers, LLMs, machine learning, deep learning, text generation, AI projects, open-source models
What you’ll learn
Build confidence with ChatGPT-level practice.
Spot patterns in Diffusion models faster.
Turn deep learning into repeatable habits.
Connect ideas to read, 2026 without the overwhelm.
Who it’s for
Students who need structure and memorable examples. Skimmers and deep divers both win—chapters work standalone.
How to use it
Skim the headings, then re-read only what sparks a decision. Bonus: end sessions mid-paragraph to make restarting easy.
The 2026 tie-ins made it feel like it was written for right now. Huge win. (Side note: if you like Introduction to Computational Cancer Biology, you’ll likely enjoy this too.)
Leo Sato • Automation
Feb 16, 2026
Not perfect, but very useful. The read angle kept it grounded in current problems.
Harper Quinn • Librarian
Feb 8, 2026
I didn’t expect 101 Generative AI Projects: Diffusion Models, Transformers, ChatGPT, and Other LLMs (Paperback) to be this approachable. The way it frames AI projects made me instantly calmer about getting started.
Leo Sato • Automation
Feb 17, 2026
What surprised me: the advice doesn’t collapse under real constraints. The open-source models sections feel field-tested.
Theo Grant • Security
Feb 13, 2026
A solid “read → apply today” book. Also: read vibes.
Samira Khan • Founder
Feb 14, 2026
The book rewards re-reading. On pass two, the Generative AI connections become more explicit and surprisingly rigorous.
Theo Grant • Security
Feb 16, 2026
Fast to start. Clear chapters. Great on deep learning.
Iris Novak • Writer
Feb 13, 2026
I’ve already recommended it twice. The AI projects chapter alone is worth the price.
Harper Quinn • Librarian
Feb 17, 2026
It pairs nicely with what’s trending around excerpt—you finish a chapter and think: “okay, I can do something with this.”
Iris Novak • Writer
Feb 12, 2026
I’ve already recommended it twice. The LLMs chapter alone is worth the price.
Sophia Rossi • Editor
Feb 15, 2026
I’ve already recommended it twice. The ChatGPT chapter alone is worth the price.
Iris Novak • Writer
Feb 16, 2026
Okay, wow. This is one of those books that makes you want to do things. The open-source models framing is chef’s kiss.
Maya Chen • UX Researcher
Feb 9, 2026
I’ve already recommended it twice. The deep learning chapter alone is worth the price.
Omar Reyes • Data Engineer
Feb 13, 2026
What surprised me: the advice doesn’t collapse under real constraints. The text generation sections feel field-tested.
Maya Chen • UX Researcher
Feb 16, 2026
The wheel tie-ins made it feel like it was written for right now. Huge win.
Benito Silva • Analyst
Feb 17, 2026
This is the rare book where I highlight a lot, but I also use the highlights. The open-source models sections feel super practical.
Ava Patel • Student
Feb 8, 2026
If you care about conceptual clarity and transfer, the february tie-ins are useful prompts for further reading.
Benito Silva • Analyst
Feb 10, 2026
I didn’t expect 101 Generative AI Projects: Diffusion Models, Transformers, ChatGPT, and Other LLMs (Paperback) to be this approachable. The way it frames Generative AI made me instantly calmer about getting started.
Ava Patel • Student
Feb 14, 2026
From a structural standpoint, the text creates a coherent ladder: definitions → examples → constraints → application. That’s why the text generation arguments land.
Benito Silva • Analyst
Feb 14, 2026
It pairs nicely with what’s trending around time—you finish a chapter and think: “okay, I can do something with this.”
Noah Kim • Indie Dev
Feb 8, 2026
Fast to start. Clear chapters. Great on Generative AI.
Benito Silva • Analyst
Feb 10, 2026
It pairs nicely with what’s trending around read—you finish a chapter and think: “okay, I can do something with this.”
Maya Chen • UX Researcher
Feb 12, 2026
Okay, wow. This is one of those books that makes you want to do things. The text generation framing is chef’s kiss.
Benito Silva • Analyst
Feb 13, 2026
This is the rare book where I highlight a lot, but I also use the highlights. The Diffusion models sections feel super practical.
Iris Novak • Writer
Feb 9, 2026
Okay, wow. This is one of those books that makes you want to do things. The Diffusion models framing is chef’s kiss.
Noah Kim • Indie Dev
Feb 13, 2026
Practical, not preachy. Loved the transformers examples.
Samira Khan • Founder
Feb 11, 2026
From a structural standpoint, the text creates a coherent ladder: definitions → examples → constraints → application. That’s why the Diffusion models arguments land.
Ava Patel • Student
Feb 11, 2026
The book rewards re-reading. On pass two, the AI projects connections become more explicit and surprisingly rigorous.
Benito Silva • Analyst
Feb 12, 2026
This is the rare book where I highlight a lot, but I also use the highlights. The text generation sections feel super practical.
Noah Kim • Indie Dev
Feb 17, 2026
A solid “read → apply today” book. Also: excerpt vibes.
Omar Reyes • Data Engineer
Feb 13, 2026
What surprised me: the advice doesn’t collapse under real constraints. The machine learning sections feel field-tested.
Nia Walker • Teacher
Feb 8, 2026
The wheel tie-ins made it feel like it was written for right now. Huge win.
Ethan Brooks • Professor
Feb 10, 2026
Not perfect, but very useful. The time angle kept it grounded in current problems.
Theo Grant • Security
Feb 15, 2026
Fast to start. Clear chapters. Great on AI projects.
Iris Novak • Writer
Feb 12, 2026
I’ve already recommended it twice. The deep learning chapter alone is worth the price.
Omar Reyes • Data Engineer
Feb 17, 2026
I’m usually wary of hype, but 101 Generative AI Projects: Diffusion Models, Transformers, ChatGPT, and Other LLMs (Paperback) earns it. The ChatGPT chapters are concrete enough to test.
Maya Chen • UX Researcher
Feb 17, 2026
The 2026 tie-ins made it feel like it was written for right now. Huge win.
Leo Sato • Automation
Feb 9, 2026
I’m usually wary of hype, but 101 Generative AI Projects: Diffusion Models, Transformers, ChatGPT, and Other LLMs (Paperback) earns it. The Generative AI chapters are concrete enough to test.
Harper Quinn • Librarian
Feb 10, 2026
This is the rare book where I highlight a lot, but I also use the highlights. The transformers sections feel super practical.
Iris Novak • Writer
Feb 13, 2026
I’ve already recommended it twice. The deep learning chapter alone is worth the price.
Omar Reyes • Data Engineer
Feb 14, 2026
What surprised me: the advice doesn’t collapse under real constraints. The Diffusion models sections feel field-tested.
Nia Walker • Teacher
Feb 14, 2026
I’ve already recommended it twice. The ChatGPT chapter alone is worth the price.
Ethan Brooks • Professor
Feb 15, 2026
Not perfect, but very useful. The read angle kept it grounded in current problems.
Zoe Martin • Designer
Feb 17, 2026
Okay, wow. This is one of those books that makes you want to do things. The transformers framing is chef’s kiss.
Jules Nakamura • QA Lead
Feb 7, 2026
This is the rare book where I highlight a lot, but I also use the highlights. The machine learning sections feel super practical.
Zoe Martin • Designer
Feb 10, 2026
I’ve already recommended it twice. The AI projects chapter alone is worth the price.
Harper Quinn • Librarian
Feb 9, 2026
It pairs nicely with what’s trending around excerpt—you finish a chapter and think: “okay, I can do something with this.”
Maya Chen • UX Researcher
Feb 10, 2026
Okay, wow. This is one of those books that makes you want to do things. The machine learning framing is chef’s kiss.
Benito Silva • Analyst
Feb 13, 2026
I didn’t expect 101 Generative AI Projects: Diffusion Models, Transformers, ChatGPT, and Other LLMs (Paperback) to be this approachable. The way it frames ChatGPT made me instantly calmer about getting started.
Jules Nakamura • QA Lead
Feb 16, 2026
This is the rare book where I highlight a lot, but I also use the highlights. The open-source models sections feel super practical.
Samira Khan • Founder
Feb 14, 2026
From a structural standpoint, the text creates a coherent ladder: definitions → examples → constraints → application. That’s why the machine learning arguments land.
Noah Kim • Indie Dev
Feb 8, 2026
Practical, not preachy. Loved the text generation examples.
Benito Silva • Analyst
Feb 16, 2026
It pairs nicely with what’s trending around time—you finish a chapter and think: “okay, I can do something with this.”
Lina Ahmed • Product Manager
Feb 16, 2026
The february tie-ins made it feel like it was written for right now. Huge win.
Samira Khan • Founder
Feb 12, 2026
If you care about conceptual clarity and transfer, the 2026 tie-ins are useful prompts for further reading.
Noah Kim • Indie Dev
Feb 9, 2026
Fast to start. Clear chapters. Great on ChatGPT.
Samira Khan • Founder
Feb 8, 2026
If you care about conceptual clarity and transfer, the 2026 tie-ins are useful prompts for further reading.
Omar Reyes • Data Engineer
Feb 12, 2026
I’m usually wary of hype, but 101 Generative AI Projects: Diffusion Models, Transformers, ChatGPT, and Other LLMs (Paperback) earns it. The deep learning chapters are concrete enough to test.
Benito Silva • Analyst
Feb 8, 2026
I didn’t expect 101 Generative AI Projects: Diffusion Models, Transformers, ChatGPT, and Other LLMs (Paperback) to be this approachable. The way it frames Generative AI made me instantly calmer about getting started.
Harper Quinn • Librarian
Feb 14, 2026
It pairs nicely with what’s trending around read—you finish a chapter and think: “okay, I can do something with this.”
Maya Chen • UX Researcher
Feb 11, 2026
The february tie-ins made it feel like it was written for right now. Huge win.
Leo Sato • Automation
Feb 17, 2026
I’m usually wary of hype, but 101 Generative AI Projects: Diffusion Models, Transformers, ChatGPT, and Other LLMs (Paperback) earns it. The AI projects chapters are concrete enough to test.
Harper Quinn • Librarian
Feb 10, 2026
I didn’t expect 101 Generative AI Projects: Diffusion Models, Transformers, ChatGPT, and Other LLMs (Paperback) to be this approachable. The way it frames LLMs made me instantly calmer about getting started.
Ethan Brooks • Professor
Feb 7, 2026
What surprised me: the advice doesn’t collapse under real constraints. The Diffusion models sections feel field-tested.
Lina Ahmed • Product Manager
Feb 10, 2026
I’ve already recommended it twice. The deep learning chapter alone is worth the price.
Theo Grant • Security
Feb 8, 2026
Practical, not preachy. Loved the open-source models examples.
Samira Khan • Founder
Feb 8, 2026
The book rewards re-reading. On pass two, the LLMs connections become more explicit and surprisingly rigorous.
Theo Grant • Security
Feb 10, 2026
Fast to start. Clear chapters. Great on AI projects.
Maya Chen • UX Researcher
Feb 13, 2026
Okay, wow. This is one of those books that makes you want to do things. The Diffusion models framing is chef’s kiss.
Ethan Brooks • Professor
Feb 10, 2026
I’m usually wary of hype, but 101 Generative AI Projects: Diffusion Models, Transformers, ChatGPT, and Other LLMs (Paperback) earns it. The LLMs chapters are concrete enough to test.
Maya Chen • UX Researcher
Feb 11, 2026
I’ve already recommended it twice. The Generative AI chapter alone is worth the price.
Noah Kim • Indie Dev
Feb 14, 2026
Practical, not preachy. Loved the Diffusion models examples.
Zoe Martin • Designer
Feb 12, 2026
I’ve already recommended it twice. The Generative AI chapter alone is worth the price.
Harper Quinn • Librarian
Feb 11, 2026
It pairs nicely with what’s trending around time—you finish a chapter and think: “okay, I can do something with this.”
Ava Patel • Student
Feb 11, 2026
If you care about conceptual clarity and transfer, the wheel tie-ins are useful prompts for further reading. (Side note: if you like Generative Adversarial Networks (GANs) Explained, you’ll likely enjoy this too.)
Zoe Martin • Designer
Feb 13, 2026
Okay, wow. This is one of those books that makes you want to do things. The machine learning framing is chef’s kiss.
Theo Grant • Security
Feb 10, 2026
Fast to start. Clear chapters. Great on LLMs.
Benito Silva • Analyst
Feb 16, 2026
It pairs nicely with what’s trending around read—you finish a chapter and think: “okay, I can do something with this.”
Lina Ahmed • Product Manager
Feb 16, 2026
Okay, wow. This is one of those books that makes you want to do things. The machine learning framing is chef’s kiss.
Ava Patel • Student
Feb 11, 2026
From a structural standpoint, the text creates a coherent ladder: definitions → examples → constraints → application. That’s why the transformers arguments land.
Benito Silva • Analyst
Feb 15, 2026
I didn’t expect 101 Generative AI Projects: Diffusion Models, Transformers, ChatGPT, and Other LLMs (Paperback) to be this approachable. The way it frames deep learning made me instantly calmer about getting started.
Ava Patel • Student
Feb 12, 2026
The book rewards re-reading. On pass two, the deep learning connections become more explicit and surprisingly rigorous.
Benito Silva • Analyst
Feb 8, 2026
It pairs nicely with what’s trending around time—you finish a chapter and think: “okay, I can do something with this.”
Harper Quinn • Librarian
Feb 14, 2026
I didn’t expect 101 Generative AI Projects: Diffusion Models, Transformers, ChatGPT, and Other LLMs (Paperback) to be this approachable. The way it frames LLMs made me instantly calmer about getting started.
Maya Chen • UX Researcher
Feb 16, 2026
I’ve already recommended it twice. The LLMs chapter alone is worth the price.
Leo Sato • Automation
Feb 9, 2026
Not perfect, but very useful. The excerpt angle kept it grounded in current problems. (Side note: if you like Foundations of Graphics & Compute - Volume 3: Computing (Hardback), you’ll likely enjoy this too.)
Ava Patel • Student
Feb 15, 2026
The book rewards re-reading. On pass two, the ChatGPT connections become more explicit and surprisingly rigorous.
Benito Silva • Analyst
Feb 16, 2026
This is the rare book where I highlight a lot, but I also use the highlights. The text generation sections feel super practical.
Lina Ahmed • Product Manager
Feb 10, 2026
The 2026 tie-ins made it feel like it was written for right now. Huge win.
Noah Kim • Indie Dev
Feb 10, 2026
A solid “read → apply today” book. Also: read vibes.
Nia Walker • Teacher
Feb 10, 2026
The 2026 tie-ins made it feel like it was written for right now. Huge win.
Samira Khan • Founder
Feb 9, 2026
If you care about conceptual clarity and transfer, the february tie-ins are useful prompts for further reading. (Side note: if you like Generative Adversarial Networks (GANs) Explained, you’ll likely enjoy this too.)
Harper Quinn • Librarian
Feb 12, 2026
This is the rare book where I highlight a lot, but I also use the highlights. The Diffusion models sections feel super practical.
Noah Kim • Indie Dev
Feb 12, 2026
A solid “read → apply today” book. Also: time vibes.
Zoe Martin • Designer
Feb 15, 2026
Okay, wow. This is one of those books that makes you want to do things. The transformers framing is chef’s kiss.
Sophia Rossi • Editor
Feb 9, 2026
I’ve already recommended it twice. The ChatGPT chapter alone is worth the price.
Maya Chen • UX Researcher
Feb 17, 2026
The february tie-ins made it feel like it was written for right now. Huge win.
Ethan Brooks • Professor
Feb 12, 2026
What surprised me: the advice doesn’t collapse under real constraints. The open-source models sections feel field-tested.
Omar Reyes • Data Engineer
Feb 16, 2026
I’m usually wary of hype, but 101 Generative AI Projects: Diffusion Models, Transformers, ChatGPT, and Other LLMs (Paperback) earns it. The AI projects chapters are concrete enough to test.
Ava Patel • Student
Feb 9, 2026
From a structural standpoint, the text creates a coherent ladder: definitions → examples → constraints → application. That’s why the open-source models arguments land.
Theo Grant • Security
Feb 11, 2026
Fast to start. Clear chapters. Great on LLMs.
Maya Chen • UX Researcher
Feb 17, 2026
Okay, wow. This is one of those books that makes you want to do things. The open-source models framing is chef’s kiss.
Leo Sato • Automation
Feb 11, 2026
Not perfect, but very useful. The time angle kept it grounded in current problems.
Zoe Martin • Designer
Feb 15, 2026
Okay, wow. This is one of those books that makes you want to do things. The open-source models framing is chef’s kiss.
Theo Grant • Security
Feb 8, 2026
Practical, not preachy. Loved the Diffusion models examples.
Maya Chen • UX Researcher
Feb 12, 2026
The february tie-ins made it feel like it was written for right now. Huge win.
Leo Sato • Automation
Feb 17, 2026
Not perfect, but very useful. The read angle kept it grounded in current problems.
Samira Khan • Founder
Feb 10, 2026
The book rewards re-reading. On pass two, the AI projects connections become more explicit and surprisingly rigorous.
Harper Quinn • Librarian
Feb 16, 2026
This is the rare book where I highlight a lot, but I also use the highlights. The machine learning sections feel super practical.
Ava Patel • Student
Feb 13, 2026
From a structural standpoint, the text creates a coherent ladder: definitions → examples → constraints → application. That’s why the open-source models arguments land.
Nia Walker • Teacher
Feb 16, 2026
I’ve already recommended it twice. The Generative AI chapter alone is worth the price.
Benito Silva • Analyst
Feb 12, 2026
It pairs nicely with what’s trending around excerpt—you finish a chapter and think: “okay, I can do something with this.”
Lina Ahmed • Product Manager
Feb 14, 2026
The february tie-ins made it feel like it was written for right now. Huge win.
Theo Grant • Security
Feb 16, 2026
Practical, not preachy. Loved the transformers examples.
Demo thread: varied voice, nested replies, topic-matching language. Replace with real community posts if you collect them.
faq
Quick answers
Themes include Generative AI, Diffusion models, ChatGPT, transformers, LLMs, plus context from read, 2026, time, february.
Use the Buy/View link near the cover. We also link to Goodreads search and the original source page.
Yes—use the Key Takeaways first, then read chapters in the order your curiosity pulls you.
Try 12 minutes reading + 3 minutes notes. Apply one idea the same day to lock it in.
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