crochet slip dress Gabriela Hearst - Yeshara Crochet Stars Maxi Slip Dress in Multi Cashmere - Multi - S
SKU: 72908217471
crochet slip dress

crochet slip dress Gabriela Hearst - Yeshara Crochet Stars Maxi Slip Dress in Multi Cashmere - Multi - S

Sale price$26.62 Regular price$29.58
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Description

crochet slip dress Gabriela Hearst - Yeshara Crochet Stars Maxi Slip Dress in Multi Cashmere - Multi - SPaying significance to L'toile XVII of the Major Arcana of the Tarot de Marseille, The Yeshara Crochet Stars Maxi Slip Dress exudes quiet radiance. This extraordinary piece is hand crocheted in cognac cashmere and adorned with individually crafted stars, each one a testament to artisanal excellence. Every dress is meticulously made by Madres & Artesanas in Bolivia, honoring ancestral craftsmanship and the sacred rhythm of handmade creation. This

Paying significance to L'Étoile XVII of the Major Arcana of the Tarot de Marseille, The Yeshara Crochet Stars Maxi Slip Dress exudes quiet radiance. This extraordinary piece is hand-crocheted in cognac cashmere and adorned with individually crafted stars, each one a testament to artisanal excellence. Every dress is meticulously made by Madres & Artesanas in Bolivia, honoring ancestral craftsmanship and the sacred rhythm of handmade creation.

This luxury cashmere slip dress represents the pinnacle of conscious craftsmanship The crochet star pattern creates a celestial motif that catches light beautifully, while the maxi length silhouette drapes with exceptional fluidity.

Details:

• 100% Cashmere - sourced from the finest mills practicing sustainable production

• Hand-crocheted construction with individually crafted star appliqués

• Front zipper closure for ease of wear

• Italian sizing - runs true to size with a relaxed slip dress fit

• Made in Italy with components crafted in Bolivia

• Limited production quantities in line with our sustainability values

Each Yeshara dress embodies Gabriela Hearst's commitment to supporting women's cooperatives and preserving traditional craftsmanship. The cognac-hued cashmere offers exceptional softness, natural temperature regulation, and hypoallergenic properties. This investment piece is designed to be cherished for generations, combining timeless design with meaningful provenance.

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SKU: 72908217471

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R. Cote
Lexington, US
★★★★★ 5
Before GPT can chat, it has to learn.
Format: Paperback
One of the most comprehensive guides to AI and deep learning available. All concepts covered clearly and concisely with illustrations. Complex concepts are broken down into understandable terms. Even though ML and AI require some complex math, you won’t need it to get idea of what’s going on inside the computer’s “brain”. I use this as a reference when teaching AI concepts and preparing presentations. I highly recommend it
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Reviewed in the United States on April 5, 2025
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Rafael Azevedo Souza Costa
Lexington, US
★★★★★ 5
Great examples and practical explanations
Format: Paperback
Excellent book. Highly recommend
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Reviewed in the United States on May 19, 2025
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Thomas
West Palm Beach, US
★★★★★ 5
Great for intuitive understanding
Format: Paperback
Amazing book. Great examples and diagrams. If you're looking to get an intuitive grasp of deep learning, look no further. If you're an engineer looking to apply it, I would recommend pairing this with one of the more technical canonical texts and a programming focused book.
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Reviewed in the United States on May 4, 2024
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La Monte HP Yarroll
Draper, US
★★★★★ 5
Taught me backpropagation
Format: Paperback
I'm finding this book a great reference to supplement Syracuse IST 691 Deep Learning in Practice. In particular, its explanation of backpropagation is the clearest I have found yet, and that even includes 3 Blue 1 Brown, which always does excellent explanations.
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Reviewed in the United States on April 13, 2025
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3rd Act
Los Angeles, US
★★★★★ 5
An Easy Read
Format: Paperback
A good narrative description of how the various systems work. Good for getting a conceptual understanding. No math to speak of, and if you want it, you can refer to the references cited, or your other favorite machine learning book.
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Reviewed in the United States on May 7, 2024

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