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bot chien gion ottogi 500gBt chin gin Ottogi l s kt hp gia cc loi bt v gia v to thnh bt chin a nng vi cht lng dinh dng cao, gin rm, xp mm, an ton tin dng, chay mn u dng c. Thch hp dng lm cc mn chin, rn gip tng thm phn hp dn. Sn phm khng ch mang li v gin rm thm ngon m cn lm cho mn n c mu vng m bt mt, hp dn v gic. Sn phm c sn xut theo cng ngh hin i Ottogi Hn Quc, khng cha ha cht, cht bo qun c hi, m bo an ton cho sc khe ngi tiu dng. Thnh phn: Bt la m (67,8%), bt bp (25%), bt go,
Bột chiên giòn Ottogi là sự kết hợp giữa các loại bột và gia vị tạo thành bột chiên đa năng với chất lượng dinh dưỡng cao, giòn rụm, xốp mềm, an toàn tiện dụng, chay mặn đều dùng được.
Thích hợp dùng để làm các món chiên, rán giúp tăng thêm phần hấp dẫn. Sản phẩm không chỉ mang lại vị giòn rụm thơm ngon mà còn làm cho món ăn có màu vàng ươm bắt mắt, hấp dẫn vị giác.
Sản phẩm được sản xuất theo công nghệ hiện đại Ottogi Hàn Quốc, không chứa hóa chất, chất bảo quản độc hại, đảm bảo an toàn cho sức khỏe người tiêu dùng.
Thành phần: Bột lúa mì (67,8%), bột bắp (25%), bột gạo, bột nở, muối i-ốt, bột tỏi, phẩm màu.
Khối lượng tịnh: 500g
Bảo quản: Nơi khô ráo, thoáng mát và tránh ánh nắng mặt trời
Hạn sử dụng: 12 tháng kể từ ngày sản xuất
Hướng dẫn sử dụng:
Bước 1: Khuấy bột và tạo lớp áo bột
- Rau củ hoặc cá, tôm, mực, rửa sạch và để ráo nước
- Bớt lại một ít bột khô và hòa 150g bột chiên với 240ml nước và khuấy đều.
- Rau củ hoặc cá, tôm, mực lăn qua lớp bột khô sau đó nhúng vào bột đã khuấy tạo lớp áo chiên,
Bước 2: Cách chiên để giòn ngon
- Rau củ chiên trong dầu nóng 150~160 độ C, các loại hải sản chiên 170~180 độ C
Lưu ý: Dùng nước lọc và lượng nước phù hợp thì món chiên mới giòn, Bột đã hòa với nước nên chiên ngay, để lâu sẽ giảm độ tươi và ít giòn.
Gợi ý món ăn:
- Tôm chiên bột
- Gà rán
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4.1 ★★★★★
Based on 28 reviews
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Product Reviews
★★★★★ 3
A Broad Overview, But Light on Modern Fine-Tuning
Format: Paperback
I'm currently really interested in fine-tuning LLMs and recently completed my first LoRA-based fine-tuning on a quantized model. I came to this book looking for more detail on fine-tuning. While it touches on the topic, I found the content didn’t quite align with the current state of the field in 2025. Techniques like LoRA, QLoRA, and PEFT weren’t really covered, and the material leaned more toward what I think are older or lower level approaches. That made it harder to connect with what I’m actually working on.
That said, when I shifted to other chapters — like the sections on prompt engineering techniques such as Chain of Thought (CoT) and Tree of Thought (ToT) — I found more value. These sections were clearer, and I picked up a few practical insights, like using few-shot examples that walk through the CoT reasoning process. That’s not something I’ve tried before, and I can see how it might help smaller models that struggle with any type of reasoning tasks.
Overall, the book feels more like a broad overview of all LLM concepts. For someone exploring many topics across the LLM ecosystem, it offers a wide-ranging introduction. But for readers like me who are actively trying to learn and apply techniques like fine-tuning and quantization, it may leave you wanting up-to-date guidance.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on August 10, 2025
★★★★★ 5
Great foundation read for security!
Format: Paperback
This book is a great read! It builds a strong foundation and I would highly recommend it for builders who are interetsed in building on LLMs and ensuring everything is secure. Security is super important and this book does it justice!
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on June 27, 2025
★★★★★ 5
Loved it
Format: Paperback
I’ve easily read dozens of tech books. I liked this one a lot. Sure, there were boring parts, but most of it was engaging, especially on dry subjects. I previously read “How AI Works” and found this more informative and way more enjoyable. I got through the 700 pages in about 5 weeks while also learning about probability and linear algebra from other books and online sources. I’d love to read something more advanced by the author, maybe getting into more modern applications. I feel more comfortable with the subject and feel I am now ready to conquer more advanced texts. I initially picked this up to give me some background before reading “How to Build a LLM (from scratch)”. I’ve ordered an intermediary Deep Learning with Python book as well, but wouldn’t mind a more advanced theory book to accompany these books. I’ll definitely be rereading sections of this book to further familiarize myself with topics like backpropagation. Highly recommend if you’re looking for a gentle, but broad introduction to the topic.
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Reviewed in the United States on November 14, 2025
★★★★★ 5
A Good Place to Start Learning AI
Format: Paperback
Diving into the world of artificial intelligence can feel like stepping into a vast, uncharted ocean, and if you're looking for a reliable vessel to navigate these waters, this book is an excellent choice. However, I must be candid—this journey is not for the faint-hearted or those hoping to breeze through. The subject of AI, with its complex algorithms and intricate theories, is notoriously challenging. You won't find yourself flipping pages at a rapid pace, as this is not a title designed for speed-reading. Instead, it demands your full attention and a willingness to engage deeply with the material.
At the heart of AI lies mathematics—a fundamental pillar that underpins the entire discipline. This book, while comprehensive, offers only a glimpse into the mathematical framework that drives artificial intelligence. But don’t be disheartened by this. Think of it as a solid foundation, a primer that will arm you with the essential concepts needed before you delve deeper into the more advanced mathematical intricacies elsewhere. When you do eventually tackle those more complex equations, you'll find yourself better equipped, with a clearer understanding of the principles at play.
I should also mention that I'm no stranger to Andrew's work. Having explored some of his other writings, I can confidently say that he possesses a unique flair for communication. His ability to distill complex ideas into accessible language, without losing the essence of the subject, is truly commendable. Andrew writes with a certain finesse and sophistication that makes even the most daunting topics seem approachable. His style is not just informative, but also engaging, with a touch of elegance that sets his work apart from others in the field.
In summary, while the path to mastering AI is undeniably steep, this book serves as an invaluable guide. It’s not just a starting point; it’s a beacon for those who are serious about understanding the intricacies of artificial intelligence. Be prepared to invest time and effort, and in return, you'll gain a solid foothold in a subject that is as fascinating as it is complex.
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Reviewed in the United States on September 2, 2024
★★★★★ 5
An enjoyable, and seriously excellent, path to understanding Deep Learning...
Format: Paperback
Deep Learning is changing our world. If you want to understand more, this is a great place to start. Andrew Glassner is a talented explainer - I took his short course on Deep Learning and learned so much, but also came away impressed at how well he can make complex material so clear and engaging. And this book is jammed packed with insights, visuals, and clear explanations. The author has a playful, sometimes quirky style that shines through, which gives this tour a lot of personality as well as information. Very enjoyable reading - I felt like he captured all that was good about his course (and then some) and bottled it up in this book. There is a lot more material here than in that course, and it is well laid-out and organized so that it is easy to roam around and come back to review the pieces that matter to you.
Even if you plan to go to on to be a world-class Deep Learning engineer or mathematician, you have to start by understanding the concepts. And this book does a great job of presenting all the core ideas in a way that makes them clear and memorable.
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Reviewed in the United States on August 5, 2021
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