SKU: 38573554021

Claire McCardell: The Designer Who Set Women Free

$21.77 $24.19
Save 10%
No.2 Bestseller on salfueradeti.es >

Pay in installments of $6.05 with ShopPay, AfterPay and Klarna

Shipping Estimate
USA
  • USA
  • CAN

Ships within 48 hours · Estimated delivery Jul 28 - Aug 2

Promo Codes Available:

For Your Every Summer RSVP, with Code: SUMMER15

Description

Claire McCardell: The Designer Who Set Women FreeNamed one of The New York Times's 100 Notable Books of 2025The riveting hidden history of Claire McCardell, the most influential fashion designer you've never heard of. Claire McCardell forever changed fashion and most importantly, the lives of women. She shattered cultural norms around women's clothes, and today much of what we wear traces back to her ingenious, rebellious mind. McCardell invented ballet flats and mix and match separates, and she

Named one of The New York Times's 100 Notable Books of 2025

The riveting hidden history of Claire McCardell, the most influential fashion designer you've never heard of.

Claire McCardell forever changed fashion--and most importantly, the lives of women. She shattered cultural norms around women's clothes, and today much of what we wear traces back to her ingenious, rebellious mind. McCardell invented ballet flats and mix-and-match separates, and she introduced wrap dresses, hoodies, leggings, denim, and more into womenswear. She tossed out corsets in favor of a comfortably elegant look and insisted on pockets, even as male designers didn't see a need for them. She made zippers easy to reach because a woman "may live alone and like it," McCardell once wrote, "but you may regret it if you wrench your arm trying to zip a back zipper into place."

After World War II, McCardell fought the severe, hyper-feminized silhouette championed by male designers, like Christian Dior. Dior claimed that he wanted to "save women from nature." McCardell, by contrast, wanted to set women free. Claire McCardell became, as the young journalist Betty Friedan called her in 1955, "The Gal Who Defied Dior."

Filled with personal drama and industry secrets, this story reveals how Claire McCardell built an empire at a time when women rarely made the upper echelons of business. At its core, hers is a story about our right to choose how we dress--and our right to choose how we live.

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: 38573554021

Discover Niche Categories That Outsell

Top-Converting Item to Boost Your Average Order

4.8 ★★★★★
Based on 18 reviews
Sort
Highest Rating
Newest First
Oldest First
Product Reviews
S
Verified Purchase
Shannon
Belleville, 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
Omaha, 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
Massapequa, 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
Phoenix, 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
Chelsea, 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

recommand products

{New Arrival} Moda Ruby Star Society Sampler Curated Fat Quarter Bundle x 6 Kiss
44.00
Oracle 3157 Switchback + Load Equalizer Kit - Amber/White
64.99
Walbro 15mm OD Fuel Fitting
21.60
Rainbow Fraction Measuring Cups
24.95
Elegant Marble Gold Tablecloth 55" X 86"
24.99