Programming & Development
Programming & Software
Job Title
Deep Learning Book Review (Python / ML Learners) - Free Book + Paid Feedback (Limited Window)
What You Get (Please Read First)
- Access to a $49.99 deep learning book for $1.99 (over 95% discount) between May 25 - June 5th 2026
- Full reimbursement ($1.99) for the reduced price of the book
- $1.00 for your feedback
- A positive review/feedback on your Guru profile (helps your portfolio)
>>This is best for students and early AI learners who want the book, not for freelancers looking for normal hourly compensation.
Job Description
We are emerging publishing house building what we aim to be one of the most accessible and practical beginner-level deep learning books available today, and we are inviting a group of learners and practitioners to help review and refine it.
Most deep learning books:
- Dive too quickly into heavy math, or
- Jump into complex code without building intuition
This book takes a different approach.
It is designed to:
- Build strong intuition first
- Transition gradually into hands-on PyTorch code
- Help you understand both the “how” and the “why” behind neural networks
- Serve as a bridge from beginner to real-world application
Our goal is to create one of the best beginner-friendly deep learning books that is both intuitive and practical, not just theoretical.
Book Links
Volume 1 (this project):
https://www.amazon.com/dp/B0GKC4L5FM
Volume 2 (for reference):
https://www.amazon.com/dp/B0GKDK9F9S
Important Timeline
All bids must be submitted by: June 10
Discount window: May 25 – June 10
During this period, the book price will drop from $49.99 to $1.99 (over 95% discount).
Compensation (Important)
- Maximum bid must NOT exceed $2.99 total
You will receive:
- $1.99 reimbursement (book cost)
- $1.00 for your feedback
This is a learning-focused opportunity, not a standard paid project.
What You’ll Do
Read either:
- The full book, OR
- 2–3 chapters
- Provide a detailed review (5–15 sentences) using the structured template below.
Important Note
We are looking for honest and thoughtful feedback.
If you find the book helpful, you are welcome to share your thoughts publicly but this is completely optional and not required.
Who This Is For
- Students learning AI/ Machine Learning / Deep Learning
- Python developers exploring AI
- Freelancers working with ML, data, or automation
- Self-learners entering AI, Python, PyTorch, Deep Learning
- College students in AI programs
- Students trying to get into AI / ML / DL
Requirements
- Interest in AI / Machine Learning / Deep Learning / Artificial Neural Networks
- Ability to write clear, structured feedback in English
- Active Amazon account (you will purchase the Kindle eBook during the discount window)
How to Apply
Please include:
- Why you’re interested in deep learning
- Whether you prefer:
- Full book review
- Selected chapters
Reviewer Template (Copy, Fill, Submit)
Instructions:
Write 10–15 sentences total. Use the prompts below to guide you, but write naturally in your own words.
1. Your Background (1–2 sentences)
“I am currently [your background], and I’ve been exploring machine learning/deep learning for [time or reason].”
2. What You Understood Better (2–3 sentences)
“After reading this book, I understood [specific concept(s)] much better.
The explanation of [topic] helped clarify [what was confusing before].”
3. Concepts That Clicked (2–3 sentences)
“One part that really clicked for me was [specific example, analogy, or section].
The way it was explained made it easier to connect theory with actual understanding.”
4. Approachability (2–3 sentences)
“What I liked most is how approachable the book is.
Compared to other deep learning resources, this one [easier to follow / more intuitive / less overwhelming].”
5. Code Quality & Practical Value (2–3 sentences)
“The code examples were [clear / practical / easy to follow].
I found the [PyTorch examples / step-by-step approach] especially useful for understanding how things work in practice.”
6. Comparison to Other Resources (2–3 sentences)
“I’ve looked at other resources like [course/book/video], and this book stands out because [difference].
It feels more [practical / beginner-friendly / structured].”
7. Final Impression (1–2 sentences)
“Overall, I would recommend this book to [target audience].
It’s a great starting point for anyone trying to understand deep learning without getting overwhelmed.”
Important:
Use this as a guide only. Do not copy it exactly- write in your own words.
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