SKU: 6901010012

Siliconen beschermhoesje in druppelvorm met hanglus voor Apple AirTag (rood)

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Description

Siliconen beschermhoesje in druppelvorm met hanglus voor Apple AirTag (rood)Bescherm je Apple AirTag tegen krassen en stootjes met dit zachte siliconen hoesje in druppelvorm (rood). De tracker zit volledig ingesloten en de meegeleverde hanglus klik je zo aan een tas, sleutelbos of rugzak. Specificaties Materiaal: zachte siliconen, niet toxisch en geurloos Kleur: rood Compatibel: Apple AirTag Bevestiging: hanglus Levering: los beschermhoesje (zonder AirTag) Waarvoor gebruik je dit Apple AirTag aan een tas, sleutelbos of rugzak

Bescherm je Apple AirTag tegen krassen en stootjes met dit zachte siliconen hoesje in druppelvorm (rood). De tracker zit volledig ingesloten en de meegeleverde hanglus klik je zo aan een tas, sleutelbos of rugzak.

Specificaties

  • Materiaal: zachte siliconen, niet-toxisch en geurloos
  • Kleur: rood
  • Compatibel: Apple AirTag
  • Bevestiging: hanglus
  • Levering: los beschermhoesje (zonder AirTag)

Waarvoor gebruik je dit

  • Apple AirTag aan een tas, sleutelbos of rugzak hangen
  • Sleutels, koffer of fiets terugvinden via Zoek mijn
  • AirTag beschermen tegen krassen en valschade
  • Een verzorgde druppelvorm in plaats van een losse tracker

Installatie

🟢 Moeilijkheidsgraad: makkelijk. Reken op ongeveer 2 minuten en je hebt geen gereedschap nodig: AirTag in het hoesje klikken en bevestigen.

Veelgestelde vragen

Past dit hoesje zeker op mijn Apple AirTag?
Ja, dit hoesje is gemaakt voor de Apple AirTag (de ronde tracker van Apple). Het is niet bedoeld voor andere trackers met afwijkende maten.

Zit de AirTag stevig vast?
Ja. De AirTag wordt all-round ingesloten en zit achter een stevige knopsluiting, zodat hij stevig op zijn plek blijft.

Hoe doe ik de AirTag erin?
Open het hoesje, leg de AirTag erin en klik of druk het dicht. Daarna bevestig je het via de meegeleverde lus of ring. Geen gereedschap nodig, klaar in ongeveer 2 minuten.

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SKU: 6901010012

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Zay
Bozeman, 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
Omaha, 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.
Chelsea, 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
Bozeman, 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
Cuba, 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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