SKU: 33412041471

Burly Brand Narrow Ape 12in - Black

Sale price$177.30 Regular price$197.00
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Description

Burly Brand Narrow Ape 12in - BlackFor a distinct new look on your narrow glide front end, the Burly Brand Narrow Ape features a narrow centered tapered design. High quality steel tubing. 3 1 2" on center knurling. Slotted and drilled for internal wiring. Stock 1" risers and clamps are accepted on 1" bars. This Part Fits: Year Make Model Submodel 1995 2010 Harley Davidson FXD Dyna Super Glide Base 2006 2017 Harley Davidson FXDB Street Bob Base 1991 1992 Harley Davidson FXDB D Dyna

For a distinct new look on your narrow glide front end, the Burly Brand Narrow Ape features a narrow centered/tapered design. High-quality steel tubing. 3 1/2" on-center knurling. Slotted and drilled for internal wiring. Stock 1" risers and clamps are accepted on 1" bars.

This Part Fits:

Year Make Model Submodel
1995-2010 Harley-Davidson FXD Dyna Super Glide Base
2006-2017 Harley-Davidson FXDB Street Bob Base
1991-1992 Harley-Davidson FXDB-D Dyna Glide Daytona Base
1991 Harley-Davidson FXDB-S Dyna Glide Sturgis Base
1992,2005,2007-2014 Harley-Davidson FXDC Super Glide Custom Base
2006 Harley-Davidson FXDCI Super Glide Custom Base
2006 Harley-Davidson FXDI35 Dyna 35th Anniversary Super Glide Base
1993-2005,2007-2009,2014-2017 Harley-Davidson FXDL Dyna Low Rider Base
1994-2000 Harley-Davidson FXDS-Conv Dyna Convertible Base
1999-2005 Harley-Davidson FXDX Dyna Super Glide Sport Base
2001-2003 Harley-Davidson FXDXT Dyna Super Glide T-Sport Base
2016-2019 Harley-Davidson XL1200C Sportster 1200 Custom Base
2016-2020 Harley-Davidson XL1200CX Roadster Base
2018-2021 Harley-Davidson XL1200NS Iron 1200 Base
2016-2020 Harley-Davidson XL1200T SuperLow 1200T Base
2016 Harley-Davidson XL1200V Seventy-Two Base
2016-2022 Harley-Davidson XL1200X Forty-Eight Base
2018-2019 Harley-Davidson XL1200XS Forty-Eight Special Base
2016-2019 Harley-Davidson XL883L SuperLow Base
2016-2022 Harley-Davidson XL883N Iron 883 Base
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SKU: 33412041471

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Zay
Charlottesville, 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
New York, 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.
Los Angeles, 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
Houston, 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
Whiting, 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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