SKU: 20184898805
dresses with boots summer

dresses with boots summer Lily

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Ships within 48 hours · Estimated delivery Oct 29 - Nov 3

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For Your Every Summer RSVP, with Code: SUMMER15

Description

dresses with boots summer LilyLimited Stock Available Click "ADD TO CART" To Get Yours Now For 50% OFF US Customers We recommend ordering 1 sizes larger The Lily Off Shoulder Beach Floral Summer Dress has fashion fans going crazy! Get ready to embrace the sun in our stunning Off Shoulder Beach Floral Summer Dress! Designed to keep you cool and stylish, this dress is your go to for beach days, vacations, or casual summer outings. With its breezy fabric and vibrant floral print,

Limited Stock Available - Click "ADD TO CART" To Get Yours Now For 50% OFF

US Customers - We recommend ordering 1 sizes larger

The Lily™ - Off-Shoulder Beach Floral Summer Dress has fashion fans going crazy! 🔥

Get ready to embrace the sun in our stunning Off Shoulder Beach Floral Summer Dress! 

Designed to keep you cool and stylish, this dress is your go-to for beach days, vacations, or casual summer outings. With its breezy fabric and vibrant floral print, you'll feel confident and comfortable wherever you go.

Don't miss out on the ultimate summer wardrobe staple that combines elegance with ease!

Why You'll Love It:  
  • Flowy, lightweight fabric for all-day comfort.
  • Chic off-shoulder design that flatters every neckline.
  • Bright floral print to brighten up your summer look.
  • Versatile style perfect for beach, brunch, or strolls.
  • Easy to dress up or down with accessories.
Specifications
Material: Polyester, Elastane
Elasticity: Slight Stretch

Note: We sell EU sizes. Please verify your size according to the size chart before completing your order for a sure comfortable fit.

Size Chest /Bust Length
XS 59-92 cm
23.5-36 in 		130 cm
51 in
S 62-95 cm
24.5-37.5 in 		131 cm
51.5 in
M 64-98 cm
25-38.5 in 		132 cm
52 in
L 66-101 cm
26-39.5 in 		133 cm
52.3 in
XL 68-103 cm
26.5-40.5 in 		134 cm
52.7 in
2XL 70-106 cm
27.5-41.5 in 		135 cm
53 in
3XL 72-109 cm
28.5-43 in 		136 cm
53.5 in
4XL 74-112 cm
29-44 in 		137 cm
54 in
5XL 76-115 cm
30-45.3 in 		138 cm
54.5 in



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FAQs

Q: Is this dress suitable for all body types?
A: Yes! Its relaxed fit and elastic neckline make it flattering for various body shapes.

 ∙ · • ⦿ • · ∙

Q: Can I machine wash this dress?
A: Absolutely! It’s easy to care for—just wash cold and hang to dry.

 ∙ · • ⦿ • · ∙

Q: What size should I choose?
A: Refer to our sizing chart for the perfect fit; sizes range from XS to 5XL.

Shipping Notes
  • Free Standard Shipping on $100+ Orders to the USA.
  • Except Preorder products are shipped in 48 hours.
  • Delivery to the USA:
  1. Standard Shipping : 3-10 business days
  • If time is of the essence, please consider selecting expedited delivery for faster service.
Exchange/Return Notes
  • We offer a 30-day return/exchange service after receiving.
  • Final sale items are not eligible for returns or exchanges.
  • To process your return/exchange, please contact us at [email protected]
  • Please click here for more details>>> Return & Exchange Policy
SKU: 20184898805

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4.0 ★★★★★
Based on 18 reviews
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Product Reviews
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Verified Purchase
Shannon
Waukegan, US
★★★★★ 5
The best DL/ML book I have ever seen!!
Format: Hardcover
Fantastic deep-learning book! The logic is very easy to follow, but the content is very thorough when it comes to explaining the theories behind it, making it perfect for beginners as well as math and CS students. The best DL/ML book I have ever seen!!
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on November 30, 2025
W
Verified Purchase
William P Ross
Fort Morgan, 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.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on March 15, 2017
A
Verified Purchase
Adam
Fort Morgan, 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.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on May 22, 2026
A
Verified Purchase
Amazon Customer
Los Angeles, 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!!
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on July 14, 2017
M
Verified Purchase
mackster
San Leandro, 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.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on May 15, 2018

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