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Description
TOYOTA SUPRA MK3Built for those who live life in the fast lane. Kingsley Racing Streetwear where passion meets performance. 100% combed and ring spun cotton (Heather colors contain polyester) Fabric weight: 4. 2 oz. yd. (142 g m) Pre shrunk fabric Side seamed construction Shoulder to shoulder taping Blank product sourced from Nicaragua, Mexico, Honduras, or the US This product is made especially for you as soon as you place an order, which is why it takes us a bit
Built for those who live life in the fast lane. Kingsley Racing Streetwear – where passion meets performance.• 100% combed and ring-spun cotton (Heather colors contain polyester)
• Fabric weight: 4.2 oz./yd.² (142 g/m²)
• Pre-shrunk fabric
• Side-seamed construction
• Shoulder-to-shoulder taping
• Blank product sourced from Nicaragua, Mexico, Honduras, or the US
This product is made especially for you as soon as you place an order, which is why it takes us a bit longer to deliver it to you. Making products on demand instead of in bulk helps reduce overproduction, so thank you for making thoughtful purchasing decisions!
Size guide
| LENGTH (cm) | WIDTH (cm) | CHEST (cm) | |
| S | 71.1 | 45.7 | 86.4-94 |
| M | 73.7 | 50.8 | 96.5-104.1 |
| L | 76.2 | 55.9 | 106.7-114.3 |
| XL | 78.7 | 61 | 116.8-124.5 |
| 2XL | 81.3 | 66 | 127-134.6 |
| 3XL | 83.8 | 71.1 | 137.2-144.8 |
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4.3 ★★★★★
Based on 843 reviews
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Product Reviews
★★★★★ 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
★★★★★ 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
★★★★★ 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
★★★★★ 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
★★★★★ 5
Easy to understand, makes algorithms exciting again!
Format: Kindle
Dive Into Algorithms speaks to me directly as a very intrepid beginner myself. I was given another "learn Python" book several years ago and it languishes on a shelf undisturbed to this day. Dive Into Algorithms had me hooked by the first parfait recipe.
Mr. Tuckfield explains concepts in such a way that any student can learn something. The history, physics, cooking, and math lessons teach us that algorithms are everywhere, and they're not big scary 'big data' monsters out to ruin us. Instead, they're tools to help understand the world around us.
This book has made me excited about programming again. Thank you.
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Reviewed in the United States on January 28, 2021