SKU: 88553138981
a line off the shoulder wedding dress

a line off the shoulder wedding dress Monique Off-Shoulder Long Sleeve A-line Lace Gown

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Size: 4
Size Recommendation How To Measure

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Description

a line off the shoulder wedding dress Monique Off-Shoulder Long Sleeve A-line Lace GownMADE TO ORDER ITEM Romantic and regal, the Monique Off the Shoulder Lace Bridal Gown is designed for the bride who wants timeless elegance with a modern edge. Crafted from premium lace, this gown features a beautifully structured bodice with internal boning for a corset inspired fit that provides both comfort and support. The sweetheart neckline is framed with delicate lace trim, flowing into sheer lace long sleeves finished with scalloped lace edging

MADE TO ORDER ITEM


Romantic and regal, the Monique Off-the-Shoulder Lace Bridal Gown is designed for the bride who wants timeless elegance with a modern edge. Crafted from premium lace, this gown features a beautifully structured bodice with internal boning for a corset-inspired fit that provides both comfort and support. The sweetheart neckline is framed with delicate lace trim, flowing into sheer lace long sleeves finished with scalloped lace edging for a refined touch. A trendy Basque waistline, inspired by the Victorian era, flatters the figure by elongating the torso before giving way to a voluminous, gathered A-line skirt. The gown flows effortlessly into a dramatic cathedral train, creating a breathtaking silhouette with every step.

Perfect for a winter wedding, Monique balances tradition and modern sophistication, making it an unforgettable choice for brides seeking a blend of romance, structure, and graceful movement.

  • Note: this is a made-to-order item, please allow 2-4 weeks for production and delivery
  • Non-stretch premium ivory lace with ivory underlay
  • Off-the-shoulder sweetheart neckline with lace trimming detail
  • Long sleeves (unlined)
  • Internal boning/corset-style bodice
  • Basque waistline
  • Full, gathered A-line skirt with a moderate train
  • Hidden back zipper
  • Limited to no stretch - we'd recommend ordering a larger size if fall between sizes (bust and waist measurements only)


Sizing Guide:

Don’t worry too much about your hip measurement for this gown because it has a full A-line skirt, the fabric flows out from the waist and doesn’t cling to the hips. What really matters most for fit is your bust and waist, since those are the areas the bodice is tailored to.

Model Info:

Isabella wears a size XS with no room to spare
Height: 5’8/173cm without heels
Bust: 32.7"/83cm
Waist: 26”/66cm
Hips: 35”/87cm - NOTE: with an A-line skirt, the hips aren’t fitted, so hip size isn’t important - the only measurements that matter are your bust and waist.

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    Exchange/Return Notes
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    SKU: 88553138981

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    4.2 ★★★★★
    Based on 24 reviews
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    A
    Verified Purchase
    Amazon Customer
    Battle Creek, US
    ★★★★★ 4
    Just learning it
    Format: Paperback
    Nice learning book just have to finish it
    WAS THIS REVIEW HELPFUL?YesReportShare
    Reviewed in the United States on December 10, 2025
    K
    Verified Purchase
    Kindle Customer
    Alexandria, US
    ★★★★★ 5
    Very useful book
    Format: Paperback
    I use it for the machine learning class I teach.
    WAS THIS REVIEW HELPFUL?YesReportShare
    Reviewed in the United States on May 3, 2026
    T
    Verified Purchase
    Tommy Jonsson
    New York, US
    ★★★★★ 5
    Cover many areas in detail and recommendations for more to read for what's outside
    Format: Paperback
    Good book!
    WAS THIS REVIEW HELPFUL?YesReportShare
    Reviewed in the United States on May 4, 2026
    M
    Verified Purchase
    Moses Kayanda
    Cuba, US
    ★★★★★ 5
    One of the best machine learning books...
    Format: Paperback, Format: Paperback
    Machine Learning can often be intimidating whether you are starting out or already a practitioner. It is easy to get stuck on one concept, walk away frustrated, or just copy that code you find on StackOverflow without really understanding what it does. What the authors of this book, Machine Learning with PyTorch and Scikit-Learn, have managed to do is to keep the reader engaged giving a deeper illustration as to how the concepts work. In this book, you get practical code examples, a detailed explanation of how the various library tools work, and exposure to the mathematical concepts behind machine learning algorithms. In addition, what I like about the book unlike many machine learning books is that the authors have managed to intuitively explain how each algorithm works, how to use them, and the mistake you need to avoid. I have not read a Machine Learning book that better explains Transformers as this one does. The authors have managed to give a detailed dive into this model architecture through well-explained codes and illustrations. As a reader, you walk away having intuitively grasped the concepts of attention and self-attention in ways that will make this crucial NLP architecture clear. You get exposed to pre-trained models from HuggingFace library which really helps to have that hands-on experience working with large datasets. As they have done throughout the book, the authors have broken down those complex mathematical operations into simple explanations that are easy to follow. What I generally like about the book is how it seamlessly connects all the chapters, not throwing off the reader. There are numerous external resources quoted throughout the book. This helps spark that curiosity to dig deeper. In addition, you get introduced to PyTorch, getting exposed to all those sophisticated libraries that help the reader learn how to maximize their compute power. I would say it is not intimidating at all even if you have not used PyTorch before. I would recommend this book to anybody seeking a textbook that is both easy to read and modern in its content. If were to rate the book I will give it a 10/10 as it really applies to both beginners and experienced practitioners, covers all the concepts one needs to apply in their operations, and acts as a quick reference.
    WAS THIS REVIEW HELPFUL?YesReportShare
    Reviewed in the United States on March 1, 2022
    G
    Verified Purchase
    Gabe Rigall
    Waukegan, US
    ★★★★★ 5
    Thorough Primer for Machine Learning and PyTorch
    Format: Paperback
    BLUF: A thorough primer for machine learning enthusiasts with plenty of theory to underscore its many practical examples. A definite must-have for anyone looking to add PyTorch to their machine learning tool belt. PROS: - Extremely thorough (if not comprehensive). I really appreciate that this book doesn't just thrust one into building models with PyTorch. It starts at the "beginning" and provides examples, theory, additional resources, and citations along the way. - Theory. Those whose calculus and linear algebra courses ended many years ago will appreciate (if not remember exactly) the mathematical theory and notation that accompanies almost every paragraph. This book gives one the opportunity to "dig deeper" or stay in the shallows until the notation stops. - Python. Rather than simply utilizing Scikit-Learn to illustrate concepts and introduce models, this book contains many sections where models (such as a Perceptron) are coded from the ground up so the reader can fully understand the underlying mechanics. Python enthusiasts will nerd out. Parents of small children might want to skip a few pages. - Graphs, charts, and graphics. There are plenty of places where a drier text might have foregone the use of graphs. This text does not. It does however refrain from overusing them. - PyTorch. This should be obvious from the title, but this text prioritizes PyTorch instead of TensorFlow. This is especially helpful for those looking for an alternative to Keras and TensorFlow as the PyTorch API is very user-friendly. CONS: - Almost too much code. This isn't a true "con" but anyone wanting to emulate or follow along with the examples would do well to get the digital edition so they can copy and paste. - Length and complexity. Anyone hoping for a "quick read" or a "quick start guide" will be disappointed. This book hovers somewhere between an undergraduate primer and a graduate-level text for length and readability. This is not to say that it's difficult to read, merely that there are other "quick start" / "practical" texts out there that cater more to a lay audience.
    WAS THIS REVIEW HELPFUL?YesReportShare
    Reviewed in the United States on February 26, 2022

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