dresses short dresses LaDivine CD0132 Short Lace Off Shoulder Homecoming Dress
SKU: 94417926809
dresses short dresses

dresses short dresses LaDivine CD0132 Short Lace Off Shoulder Homecoming Dress

Sale price$19.91 Regular price$22.12
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Size: 4

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Description

dresses short dresses LaDivine CD0132 Short Lace Off Shoulder Homecoming DressPlayful lace and a flattering offshoulder neckline define the OfftheShoulder Lace Prom Short Dress, a minilength party dress made for prom, homecoming, and semiformal events. The offshoulder neckline frames the shoulders while embroidered lace gives texture without bulk. An attached rhinestone belt gently defines the waist and adds a touch of refined detail. Soft cup inserts in the fully lined bodice offer light support and comfort for dancing or

Playful lace and a flattering off‑shoulder neckline define the Off‑the‑Shoulder Lace Prom Short Dress, a mini‑length party dress made for prom, homecoming, and semi‑formal events. The off‑shoulder neckline frames the shoulders while embroidered lace gives texture without bulk. An attached rhinestone belt gently defines the waist and adds a touch of refined detail. Soft cup inserts in the fully lined bodice offer light support and comfort for dancing or standing. The above‑knee length keeps the silhouette youthful and easy to move in. A back zipper closure helps secure the fit smoothly without fuss. This dress works well for anyone who wants a balanced blend of structure and playful detail in a short formal dress.

Key Features:


A‑Line Silhouette: Sweeps from a fitted bodice into a flattering mini hem
Off‑Shoulder Neckline: Frames the shoulders and collarbone
Embroidered Lace Fabric: Adds texture with refined detail
Rhinestone Belt: Soft waist definition with subtle sparkle
Soft Cup Inserts: Light support for comfort
Back Zipper Closure: Smooth and secure fit

Available Colors:

Ice Blue, Blush, Burgundy, Champagne, Lilac, White 

Perfect for Special Occasions!

Ideal for prom, homecoming, cocktail parties, dance events, semi‑formal celebrations, and graduation. 

Details:


Silhouette & Fit: A‑line mini
Neckline & Sleeves: Off‑shoulder
Length: Above knee
Fabric (Shell): Lace, tulle
Lining: Fully lined with soft cup support
Closure: Back zipper
Embellishment: Rhinestone belt
Sizes: XS, S, M, L, XL, 2XL, 3XL, 4XL
Occasions: Prom, homecoming, cocktail party, dance, wedding guest

Care Tips:

  • Professional Cleaning Only: Preserves intricate beading and embroidery
  • Store on a Padded Hanger: Maintains shape and prevents fabric stress
  • Avoid Moisture & Heat: Protects metallic detailing from damage
  • Handle With Care: Embellishments are delicate and may snag

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SKU: 94417926809

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4.8 ★★★★★
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William P Ross
Port Orchard, US
★★★★★ 5
Comprehensive Look At An Incredibly Complex Topic
Format: Hardcover
Deep Learning is an advanced book with great explanations and details. There is a heavy math focus with the book's beginning chapters detailing the necessary linear algebra and probability that one will need to understand deep learning. I liked that the author's chose to cover only the parts of these subjects which are relevant to deep learning. There are many interesting philosophical sections in the book as well. Just about when I was feeling overwhelmed with the complexity of the mathematics the authors take a step back and cover the foundations of deep learning such as borrowing concepts from human learning. There was an interesting dicussion about the early studies done on the vision of cat's and monkey's in the 1970s. The text covers the entire history of deep learning and the bibliography is hundreds of sources. It is clear this is the most comprehensive text available about deep learning. For anybody interested in this topic this book is a mandatory read. There are sections about machine learning as well, which makes sense because deep learning is a subset of machine learning. These sections focused on the machine learning concepts which are most relevant to deep learning. The book was well organized and divided into three parts which cover mathematics related to deep learning, typical deep learning techniques, and then more experiment learning techniques. Often the author's state when a technique works well or when it does not, and which types of data works best for the technique. Just a warning, the math in this book is highly complex. It requires a lot of work to go through this book, but the effort will be well rewarded.
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Reviewed in the United States on March 15, 2017
A
Verified Purchase
Adam
New York, US
★★★★★ 4
Too Dry.
Format: Hardcover
This was a required textbook for my class in college. I think it was too dry. The book titled Deep Learning: From Curiosity To Mastery is much more approachable.
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Reviewed in the United States on May 22, 2026
A
Verified Purchase
Amazon Customer
Massapequa, US
★★★★★ 5
Comprehensive! The Bible of Deep Learning!
This book has by far surpassed my expectations! I have purchased many machine learning and deep neural network books in the past, but nothing has ever come close to this book! First of all, it is written by the fathers of Deep Learning, and is therefore an authority. Secondly, the book is broken into three parts: 1. A math overview and refresher. 2. Deep Learning applications and 3. Research in Deep Learning. I can't help but go through this book from front to back. It is a smooth read, and every sentence written is meaningful. These guys know their stuff! And after you read this book, YOU WILL ALSO know your stuff! If you feel daunted by the price, just remember, you get what you pay for! I'd say they could easily charge about $300+ for this book, but they are doing everyone a very kind favor by ONLY charging this reasonable amount. You get A LOT of bang for your buck with this purchase. I hesitated at first about buying this book because of the price, but I am soooooo happy that I did! Worth every penny! Look no further, get this book and start your Deep Learning journey!!
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Reviewed in the United States on July 14, 2017
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mackster
Carnegie, US
★★★★★ 1
A rushed, poorly written guide of how the "experts" can't really explain what Deep Learning is
Format: Hardcover
This book, in every sense of the word, is rushed. I think the authors wanted to establish themselves as leaders of this young-ish field, but does so by sacrificing quality. It also shows that Deep Learning theory has been there for a long time, known by another name called Neural Networks. The interesting algorithms are of MLP, Back Propagation and the classical neural networks. The optimization methods such as Adam are the ones that are new and interesting, and the only ones worthy of in this book. So, essentially, what you get from this book is use A for X, B for Y and C for Z type of dry, un-intuitive, badly written waste of paper. As for the structure of the book, it's like an example of how not to structure a book. It has some linear algebra, probability at the start (not good enough, and confuses more people and wastes paper). Goes on to prove other algorithms such as PCA (yeah, ok!). Then, talks about how this architecture works for this and that architecture. So, yeah, if you really want to try out deep learning, don't buy this book. Set up Tensorflow/pytorch/ other library, run the tutorials, find an architecture for the problem you are interested in and start tweaking that. You will have far more fun and would have saved your money. The praise that this book gets is beyond me. Did Musk even read this book? I doubt it.
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Reviewed in the United States on May 15, 2018
S
Verified Purchase
Stergios Papadimitriou
Port Orchard, US
★★★★★ 5
The classic textbook on Deep Learning
Format: Hardcover
Deep Learning is the promising direction towards general purpose effective artificial intelligence. There is an explosion of fruitful research in recent years and a lot of applications pursued mainly from technology giants as Google, Amazon, etc. and outstanding research institutions. The book "Deep Learning " by Ian Goodfellow, Yoshua Bengio, Aaron Gourville, is an excellent piece of work. They manage to present rather difficult things in an understandable manner. The theoretical presentation is outstanding typical of "classic" books. Also, the book stays close to the practical applicability of all the methods and discusses applications extensively. There are a lot of other useful books on deep learning that follow a more practical approach by focusing on a particular deep learning software package, but this one book is certainly much more essential since it provides the required theoretical background in order to be able to do serious work on deep learning. I consider the book as "must have" for anyone that works on deep learning either in an academic or in an industrial environment.
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Reviewed in the United States on August 25, 2018

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