SKU: 97906417634
1980s party dress

1980s party dress 1980s Strapless Party Dress, Size-6 – MARTINI CONSIGNMENT

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Description

1980s party dress 1980s Strapless Party Dress, Size-6 – MARTINI CONSIGNMENTYear: Spring 1992 Labels: Bob Mackie & Bergdorf Goodman Color: Ivory, Yellow, Green & Orange Fabric: Lace, Organza & Tulle Lining: Rayon Marked Size: Not Marked Measurements: Bust 36" Waist 26" Description: 1992 party dress by Bob Mackie, a playful and romantic confection that perfectly captures the eras love of fantasy and texture. The strapless bodice is constructed in a vivid printed organza, layered beneath an intricate overlay of white floral

Year: Spring 1992

Labels: Bob Mackie & Bergdorf Goodman 

Color: Ivory, Yellow, Green & Orange

Fabric: Lace, Organza & Tulle

Lining: Rayon

Marked Size: Not Marked

Measurements: Bust-36" / Waist-26" 

Description: 1992 party dress by Bob Mackie, a playful and romantic confection that perfectly captures the era’s love of fantasy and texture. The strapless bodice is constructed in a vivid printed organza, layered beneath an intricate overlay of white floral lace. The lace creates a dimensional, almost appliqué effect, allowing the soft pastel tones—peach, citron, and pale green—to glow subtly from beneath. The sweetheart neckline enhances the feminine silhouette, while the fitted structure provides a sculpted, corset-like shape. At the waist, the dress flares dramatically into a voluminous skirt of sheer tulle, delicately dotted with raised chenille polka dots. The skirt’s airy transparency reveals the softly blended colors underneath, giving the piece a luminous, almost watercolor quality in motion. Whimsical yet refined, this is a quintessential Bob Mackie design—rich in texture, theatrical in spirit, and unmistakably 1980s in its exuberant approach to eveningwear.

Condition:  Gently Worn with no obvious damage. 

Item: #128142

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SKU: 97906417634

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Zay
Birmingham, US
★★★★★ 5
Upside down (Great)
Format: Hardcover
Was extremely relatable and a blessing I gifted this book and want it back lol but I will be ordering again
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Reviewed in the United States on October 23, 2024
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Rory Derrick
Massapequa, US
★★★★★ 5
Good book
Format: Paperback
Still working through it but I have no complaints. I have a shelf of no starch books and have not been disappointed by any. Some, of course, are better than others but this is a good book.
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Reviewed in the United States on December 2, 2021
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Cory P.
Pawtucket, US
★★★★★ 5
Dive into Algorithms is more like eating a Parfait than trying understand algorithms!
Format: Paperback
Seriously though great writing and explanation along with great history lessons. Also highly recommend for anyone working in the data science field.
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Reviewed in the United States on August 3, 2021
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Frank Gonzalez
Lake Worth, US
★★★★★ 3
Ok content, not great explanations (2.5 our of 5 stars)
Format: Paperback
I found the contents of this book to be simply ok: either too simple, or the more complicated algorithms and concepts would not be as carefully explained as they should have been. It is not a terrible book, but it feels as though the author did not go over many drafts/iterations of this work.
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Reviewed in the United States on April 7, 2024
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Ira Laefsky
Boise, US
★★★★★ 5
An Excellent Self-Discovery Approach to Learning Algorithms
Format: Paperback
I have an Ivy League Master's Degree in Computer Science although it was accomplished 35 years ago. Of course, I had to complete an ACM-type course in Algorithms and Data Structures on the undergraduate and graduate level and managed to by rote accomplish enough to satisfy these courses. But until seeing this great book I never had the feeling of gaining an understanding of the approach to learning and building algorithms and the extent to which it is an important component of all programs. By a journey of guided self-discovery the author shows, not only the necessity of algorithms and their canonical forms, but a path to understanding the construction of algorithms to accomplish common and not so common practical problems. These range from the simple to understand, e.g. implementing Russian Peasant Multiplication, to advanced and up to date topics like Machine Learning. The highest praise I can give this book is that as a journey of guided self-discovery it produces an understanding in the reader of the process of constructing and understanding these algorithms and their place in all programming.
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Reviewed in the United States on February 7, 2021

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