SKU: 85816288374

Big Panda and Tiny Dragon Sticky Note Memo Cube

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Description

Big Panda and Tiny Dragon Sticky Note Memo CubeAdd a bit of peace to your life every time you leave yourself a note or reminder with this elegant Big Panda and Tiny Dragon sticky note memo cube. STUNNING ILLUSTRATIONS: Printed on all four sides and the top of the memo cube are gorgeous illustrations from James Norburys Big Panda and Tiny Dragon to calm and inspire you. CONVENIENT SIZE: Measuring 3. 15 inches on each side, this sticky note memo cube is perfect for home or office use and fits

Add a bit of peace to your life every time you leave yourself a note or reminder with this elegant Big Panda and Tiny Dragon sticky note memo cube.

STUNNING ILLUSTRATIONS: Printed on all four sides and the top of the memo cube are gorgeous illustrations from James Norbury’s Big Panda and Tiny Dragon to calm and inspire you.

CONVENIENT SIZE: Measuring 3.15 inches on each side, this sticky note memo cube is perfect for home or office use and fits comfortably on your desk or any small surface. The cube has 800 sheets for you to tear away and stick a note wherever you need one.

ADD TO YOUR COLLECTION: Introduce even more Zen into your life with the rest of Insight Editions’ Big Panda and Tiny Dragon–themed stationery collection—Big Panda and Tiny Dragon Hardcover Journal, Big Panda and Tiny Dragon Weekly Planner Notepad, and Big Panda and Tiny Dragon Boxed Card Set (Set of 20).

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SKU: 85816288374

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4.8 ★★★★★
Based on 8 reviews
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Z
Verified Purchase
Zay
Boise, 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
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on October 23, 2024
R
Verified Purchase
Rory Derrick
Houston, 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.
Charlottesville, 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
Port Orchard, 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
Carnegie, 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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