SKU: 33038819831

SPARKLE DIAMONDS BACKDROP, Black diamonds birthday Backdrop, sparkle glitz Backdrop, diamonds rose gold backdrop, dripping glitter backdrop

$13.50 $15.00
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Ships within 48 hours · Estimated delivery Jul 10 - Jul 15

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Description

SPARKLE DIAMONDS BACKDROP, Black diamonds birthday Backdrop, sparkle glitz Backdrop, diamonds rose gold backdrop, dripping glitter backdropWelcome to our little shop! We are a couple professional designers who love to design for party Items!. We strive to provide the highest quality, excellent service and incredible lowest price for you. If you have any questions please feel free to convo us, and we will happily reply you in 24 hours. We offer digital files (you print) in ANY SIZE you need or select a printed option from the dropdown menu. We can customize with wording, size and colors

Welcome to our little shop!


We are a couple professional designers who love to design for party Items!. We strive to provide the highest quality, excellent service and incredible lowest price for you.If you have any questions please feel free to convo us, and we will happily reply you in 24 hours.


We offer digital files (you print) in ANY SIZE you need or select a printed option from the dropdown menu.


We can customize with wording, size and colors (this does not requiere an extra charge). Other customizations can be done with a small additional fee.


Select DIGITAL or PRINTED OPTION from the dropdown menu at checkout.


BACKDROP OVERVIEW ––––––––––––––––––––––––––

- Digital File only or Printed and Shipped Backdrop (select your option at checkout)

- Sizes available from the dropdown menu

- Turnaround Time 10-15 business days


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Size:

All backdrops are printed in width x height format.


If you are unsure about the size please check the images of the listing for size chart recommendations.


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Package: Rolled in a hard tube for delivery (No Wrinkles)

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Features:

Lightweight,easy handling and carry;

Wrinkle-Free;

Durable and Strong;

Intense vivid colour and realistic detail;

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About Materials:

We have the following materials:


POLYESTER CANVAS: this material is water-proof and 8oz thick, you could use damp towel to wipe stains if it gets stained, we ship it rolled up on tube.


**About FOIL/GLITTER:

Please note that this is just a graphic representation of GLITTER / FOIL. The product will NOT include actual glitter/foil, instead it will have a high resolution graphic that will print to look like glitter / foil . We would recommend professional printing or using a high quality laser printer to make our customers achieve the best results if they decide to print the files at home.


**About NEON/GLOW IN THE DARK

Please have in mind that the design shows an effect of glow in the dark, printed items will NOT actually glow in the dark.


**WHAT YOU WILL RECEIVE WITH YOUR BACKDROP PURCHASE:**


- DIGITAL FILE ONLY: A PDF and JPG file sent to your email. No physical items will shipped on this option. Printing will be needed on your own or locally.

Please type in "personalization" box or via Etsy message the size you'd like for your file and wording.


If you are looking for a custom design PLEASE message us BEFORE purchase to make sure we can do what you are asking for.**


- PRINTED OPTIONS: A physical backdrop shipped to your door. Sizes and turnaround time may vary depending on the size and your location. (5-10 business days) Monday - Friday


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PROCESSING TIME


For Digital orders: 1 - 2 business days, or 24 HRS RUSH FEE option available (Monday to Friday). Please select the option of your preference.


For Printed orders:5-10 Business Days to all US. All the printed orders must be approved before printing. Delays on the approval of proof file will delay the turnaround time.


On average, please allow 10-15 business days for US deliveries once your backdrop order leaves our warehouse.


If you have a specific date you need your order by or are concerned the above time frames won't be sufficient, simply message us and we can work with you to ensure on time delivery.


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About Color:

Please note that every computer has different color and resolution settings so colors shown on your screen may vary slightly from the actual print depending on your settings. The Backdrop Shop cannot offer refunds of replacements on items that have slight color variations for this reason as this is the natural process for any printed item.We have done our best to give a color description of each backdrop.

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How to hang up the backdrop:

If you will be using a backdrop stand please select the pole pocket option, if you would be using the command wall hanger please select the eyelets option.

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ORDERING


1. Purchase the item and complete.


2. IN NOTES TO THE SELLER BOX

Please specify all wording and details you would like for your purchase.


For example:

- Size

- Colors

- Party Theme

- Name

- Age

- Wording you want on the design


3. PROOF & REVISE FOR PRINTED BACKDROPS

You'll receive a proof of your design after purchase within 1-3 business days via Etsy message or email if the Etsy message is not answered. You can either approve or request revisions to the design. Up to 3 revisions are included on the listed price, additional rounds of revisions incur in additional fee.


Please be aware of the proof files we send via Etsy convo, if we do not get a response regarding the approval of the product, we will send an email to your registered etsy email account. *Please approve your proof or resubmitt your order with specific changes as soon as possible after receiving it or this will delay the process.


If your event date is close, please keep an eye for the proof, otherwise Delivery will be delayed (Digital File/Proof cost will not be refunded).


Your backdrop will not be printed until you are happy with your design. We won't print without approval.


4. PROOF & REVISE FOR DIGITAL FILES

Once you approve the proof, we will send the final product. If we don't receive an approval via Etsy message or email within 3 business days, we will send the high resolution file to your registered Etsy email.


A digital file (.PDF and .JPG) high quality (100dpi is our standard, if you need higher please request) for printing will be sent to the email registered on your order within 2-3 business days from your purchase, Monday to Friday, if the proof file has been approved. If you need it sooner, message us via Etsy conversation! Rush Orders available. (24HRS Option Available).


Thanks for Shopping with us!


If you have any dissatisfaction or problems once received, Please feel free to contact us before leaving a negative feedback. We would try our best to help you solve the problem.

Wish you have a happy shopping in our store!

Thank you !


* PLEASE NOTE Customer have a total of 3-5 days after receiving the product to indicate if they had received with a factory defect, regarding the seams and finishings, eyelets or top pocket. Past this time is assumed the customer received the product in good condition and we cannot longer offer refund or change the products for a factory defect.


Thank you so much for stopping by Our Shop

Sweet Cards Store

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: 33038819831

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4.4 ★★★★★
Based on 1496 reviews
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Carnegie, US
★★★★★ 5
Excellent book, possibly currently unique in coverage of latest ideas
This book is possibly currently unique in its coverage of the latest ideas in the field of deep learning -- and it is a very convenient and good survey of fundamental concepts (linear algebra, optimization, performance metrics, activation function types), different network types (multi-layer perceptron, convolutional neural networks, and recurrent neural networks), practical considerations (data set, training and validation, implementation), and applications (comments on existing real-world/commercial uses). The final 235 pages of the content portion of the book is dedicated to topics in "Deep Learning Research", and these topics are truly at the current frontier. Another reviewer said that one could gain the same knowledge of cutting-edge research by reading all of the latest papers (from academia and industry), but the "research" section of this book offers the following: Selection of the most notable research by the very experienced authors of the book, and collection of similar research in to a broader discussion of themes, and the additional insights. The book covers very advanced and new ideas currently being explored, and it is very nice to be able to have a consistent and coherent presentation of all of those ideas. However, the book is also packed with valuable observations and pointers about more basic aspects of deep learning implementations and practices -- and such commentary is in depth and includes substantial analysis and mathematical derivation (in an intuitive presentation that often includes graphs illustrating the phenomenon). As someone with an intermediate level of knowledge and experience of neural networks, I am really grateful for this book, because seems like the ideal resource for learning cutting-edge ideas and practices, with context. The book has excellent scope and depth, and I am confident that anyone with a solid background in linear algebra, calculus, statistics, and general machine learning, and basic neural networks (multi-layer perceptrons) will find this book to be very exciting and perhaps unique in its ability to take the reader to the next level and a new frontier. I was personally excited to learn about the idea of representing the dependencies of intermediate quantities by directed graphs, and how this can be used to perform calculations for recurrent neural networks efficiently. And I think the long chapter on recurrent neural networks is very helpful. Having said all of this, I think only people with significant working knowledge and experience with neural networks and mathematics -- people whose academic or professional focus has been neural networks for at least a year or two -- would benefit from this book. This book answers a lot of the deeper questions that one is likely to have while developing a solid understanding of the fundamentals, and that's one of the book's tremendous values, but this book assumes an understanding of the fundamentals (but does briskly cover the basics). I think this book is a perfect follow-up book for the excellent book "Neural Network Design (2nd edition)" by Hagan, Demuth, Beale, and de Jesus, and I highly recommend the latter for gaining the solid background needed to have a thrilling experience with the "Deep Learning" book. In summary, I am very glad this "Deep Learning" book was written, and I think the "Deep Learning" book will be a great benefit to a lot of people, and to the evolution of the field.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on April 18, 2017
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Zygerian99
Louisville, US
★★★★★ 5
The definitive guide to becoming a researcher in the field
Format: Hardcover
This is not a coding book. I see a lot of negative reviews around the expectation that this book would teach the reader how to quickly build machine learning systems and write code. This book is not for that audience. If you just want to build applications, don't worry about how deep learning works. It's akin to needing to understand how an engine works just to drive a car. If you are looking for a coding resource, try: https://www.amazon.com/Hands-Machine-Learning-Scikit-Learn-TensorFlow/dp/1492032646/ref=sr_1_4?keywords=machine+learning+tensorflow&qid=1579608765&sr=8-4 . And even with that book, the material still goes far beyond what you need - use it as a light reference. I bought this book as an aspiring machine learning researcher, and towards that end, it is the best resource available in print (still true as of 2020). For instance: The first 5 chapters are timeless. These are things that were mostly established 20 or 30 years ago and beyond and are mostly STEM fundamentals at this point. There are whole textbooks dedicated to each of those chapters, but the authors provide a quick refresher and overview of probably 80% of what you'll encounter in deep learning. If you haven't previously learned each of these subtopics, you'll probably want to study them individually since they are the key to innovating (linear algebra, probability & stats, numerical computation, machine learning fundamentals). Chapters 6 thru 9 are the foundation of deep learning. We're about 12 years into seeing rapid change in the deep learning space, yet all of these principles and techniques still hold (many recent innovations are still relying on Convolutional models in 2020, which is the most layered/complex topics in those chapters). Therefore, I'd wager that these chapters are also fairly stable knowledge that is worth internalizing if you want to be deeply involved in the future of machine learning. Chapters after 9 are mostly experimental topics, and many of them are already the wrong strategies for optimal results. But there are interesting ideas in here that you'll often encounter in the wild, so it's good exposure to various topics. But probably not worth much of your time. And lastly, there is good history in here from people who know the space intimately. It's a good way to piece together the developments and learn the lexicon of deep learning so you can have intelligent conversation with experts.
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Reviewed in the United States on January 21, 2020
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Verified Purchase
Shannon
Omaha, 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!!
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Reviewed in the United States on November 30, 2025
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Verified Purchase
William P Ross
Birmingham, 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
Bozeman, 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

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