SKU: 13744247889

vidaXL Stufenmatten Selbstklebend 5 Stk. 65x21x4 cm Hellbraun Rechteckiger Rand

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Description

vidaXL Stufenmatten Selbstklebend 5 Stk. 65x21x4 cm Hellbraun Rechteckiger RandDiese Stufenmatten sind nicht nur eine auffllige dekorative Ergnzung Ihrer Wohnungseinrichtung, sondern schtzen Sie auch vor dem Ausrutschen beim Treppensteigen und verhindern, dass Ihre Treppe abgenutzt wird. Robust und langlebig: Polypropylen ist ein vielseitiges und robustes Material, das fr seine Stabilitt, Hitzebestndigkeit und einfache Reinigung geschtzt wird. Es wird fr eine Vielzahl von Anwendungen verwendet, darunter fr Teppiche und

Diese Stufenmatten sind nicht nur eine auffällige dekorative Ergänzung Ihrer Wohnungseinrichtung, sondern schützen Sie auch vor dem Ausrutschen beim Treppensteigen und verhindern, dass Ihre Treppe abgenutzt wird. Robust und langlebig: Polypropylen ist ein vielseitiges und robustes Material, das für seine Stabilität, Hitzebeständigkeit und einfache Reinigung geschätzt wird. Es wird für eine Vielzahl von Anwendungen verwendet, darunter für Teppiche und Haushaltsgegenstände.Lärmreduzierung: Die Treppenstufe wertet nicht nur die Ästhetik Ihrer Treppe auf, sondern reduziert auch den Lärm. Genießen Sie mit dem Treppenteppich ein ruhigeres, weicheres und sichereres Treppensteigen.Rutschfestes Design: Dank der rutschfesten Unterseite bleibt die Stufenmatte sicher auf dem Boden liegen und verhindert so ungewolltes Ausrutschen.Pflegeleicht: Die Stufenmatte ist maschinenwaschbar und daher leicht zu reinigen und zu pflegen. Gut zu wissen:Das Treppengestell ist für den einfachen Transport gerollt verpackt. Bitte geben Sie dem Produkt etwas Zeit, um perfekt gerade und flach zu werden.

  • Farbe: Hellbraun
  • Material: Nadelvlies (100 % Polypropylen)
  • Maße: 65 x 21 x 4 cm (L x B x H)
  • Florhöhe: 3 mm
  • Florgewicht: 500 g/m²
  • Mit selbstklebenden Punkten
  • Lieferumfang:
  • 5 x Stufenmatte
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SKU: 13744247889

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4.1 ★★★★★
Based on 19 reviews
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Z
Verified Purchase
Zay
Los Angeles, 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
R
Verified Purchase
Rory Derrick
San Leandro, 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
C
Verified Purchase
Cory P.
West Palm Beach, 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
F
Verified Purchase
Frank Gonzalez
Chelsea, 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
I
Ira Laefsky
Waukegan, 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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