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舊振南 鳳梨酥系列 JZN Pineapple Cake9 () 12 () 17 17 1890(16) (())()()(()) 35g *9 50
→舊振南鳳梨酥9入禮盒 (奶蛋素)
→舊振南鳳梨酥12入禮盒 (奶蛋素)
．台灣指定伴手禮，熱賣「小金磚」鳯梨酥
．台農17號金鑽鳳梨融合冬瓜醬的經典鳳梨酥
．外皮添加乳酪粉，吃起來奶香味特別濃郁
．獲得比利時世界食品品鑑大賞銀獎認證
嚴選日照充足的台農17號金鑽鳳梨為底，在入餡前充分研磨細桿鳳梨纖維，混合冬瓜醬做為內餡，滑順綿密香甜可口。外層酥皮使用高品質雞蛋與新鮮奶油拌入，再加上獨家配方乳酪粉，烤出外酥鬆又帶有濃郁奶香，內餡保留恰到好處的濕潤口感。獲得比利時世界食品品鑑大賞銀獎認證，為全年熱賣台灣指定伴手禮。
品牌介紹
舊振南餅店創始於西元1890年(清光緒16年)，傳承百年手工製餅技藝，將漢餅精神價值，演繹在送禮哲學上，讓每一份舊振南禮品，都能觸動送禮者與收禮者的內心，舊振南，將台灣味道與在地特色推廣到世界各地。身為見證歲月流轉的百年品牌，無論是伴手禮、節慶禮盒，或精緻的中式喜餅，皆能感受到舊振南漢式糕點文化精神的重視。近年來已經至的烘焙體驗課程與有趣的禮俗活動，將台灣文化記憶，感染更多海內外朋友，引領一個更為重視禮數的生活品味。
產品規格
- 產品成分：鳳梨冬瓜膏(冬瓜、麥芽糖、砂糖、鳳梨果肉、油脂(軟質棕櫚油、無水奶油)、食鹽)、麵粉、無水奶油、無鹽奶油(殺菌乳脂、水分)、糖、有鹽奶油(殺菌乳脂、水分、鹽)、奶粉、雞蛋、乾酪粉(乾酪(牛乳、鹽、乾酪菌、凝乳酵素)、乳固形物、檸檬酸)。
- 產品重量：35g/顆*9
- 保存期限：50日起
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4.9 ★★★★★
Based on 13 reviews
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Product Reviews
★★★★★ 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
★★★★★ 5
Before GPT can chat, it has to learn.
Format: Paperback
One of the most comprehensive guides to AI and deep learning available. All concepts covered clearly and concisely with illustrations. Complex concepts are broken down into understandable terms. Even though ML and AI require some complex math, you won’t need it to get idea of what’s going on inside the computer’s “brain”.
I use this as a reference when teaching AI concepts and preparing presentations.
I highly recommend it
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Reviewed in the United States on April 5, 2025
★★★★★ 5
Great examples and practical explanations
Format: Paperback
Excellent book. Highly recommend
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Reviewed in the United States on May 19, 2025
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