SKU: 60761947906

Cometic Jaguar XK6 .059in CFM-20 Exhaust Header Gasket

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Description

Cometic Jaguar XK6 .059in CFM-20 Exhaust Header GasketWithstands different combinations of cylinder head and manifold materials Withstands different combinations of cylinder head and manifold materials Will not burn through or push out Maintains a torque set Requires No Sealants Corrosion resistant This Part Fits: Year Make Model Submodel 1969 Jaguar 340 Base 1967 Jaguar 420 Base 1967 Jaguar 420 G 1951 1952 Jaguar C Type Base 1954,1956 Jaguar D Type Base 1958 1959 Jaguar Mark 1 3. 4 1960 1962,1964 Jaguar

Withstands different combinations of cylinder head and manifold materials

  • Withstands different combinations of cylinder head and manifold materials
  • Will not burn through or push out
  • Maintains a torque set
  • Requires No Sealants
  • Corrosion resistant

This Part Fits:

Year Make Model Submodel
1969 Jaguar 340 Base
1967 Jaguar 420 Base
1967 Jaguar 420 G
1951-1952 Jaguar C-Type Base
1954,1956 Jaguar D-Type Base
1958-1959 Jaguar Mark 1 3.4
1960-1962,1964 Jaguar Mark 2 3.4
1964-1967 Jaguar Mark 2 3.4 S
1960-1963,1965,1968 Jaguar Mark 2 3.8
1965,1968 Jaguar Mark 2 3.8 S
1959-1961 Jaguar Mark IX Base
1957 Jaguar Mark VII M
1957-1958 Jaguar Mark VIII Base
1963-1966 Jaguar Mark X Base
2003-2004,2006-2008 Jaguar S-Type Base
2003-2008 Jaguar S-Type R
2005 Jaguar S-Type Sport
2006 Jaguar S-Type VDP Edition
2005-2009 Jaguar Super V8 Base
2006 Jaguar Super V8 Portfolio
1983-1987,2004-2009 Jaguar Vanden Plas Base
2010 Jaguar XF Base
2009 Jaguar XF Luxury
2009 Jaguar XF Premium Luxury
2009 Jaguar XF Supercharged
1972,1974,1981-1987 Jaguar XJ6 Base
1975-1977 Jaguar XJ6 C
1975-1980 Jaguar XJ6 L
2004-2009 Jaguar XJ8 Base
2005-2009 Jaguar XJ8 L
2004-2009 Jaguar XJR Base
2007-2009 Jaguar XK Base
1950,1953-1954 Jaguar XK120 Base
1953-1954 Jaguar XK120 M
1955-1957 Jaguar XK140 Base
1955-1957 Jaguar XK140 M
1955-1957 Jaguar XK140 MC
1958-1961 Jaguar XK150 Base
1958-1961 Jaguar XK150 S
2003-2006 Jaguar XK8 Base
2006 Jaguar XK8 Victory Edition
1961-1964,1966-1968,1970-1971 Jaguar XKE Base
2003-2009 Jaguar XKR Base
2008-2009 Jaguar XKR Portfolio
2006 Jaguar XKR Victory Edition
1957 Jaguar XKSS Base
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SKU: 60761947906

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4.2 ★★★★★
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Adam
Draper, US
★★★★★ 4
Too Dry.
Format: Hardcover
This was a required textbook for my class in college. I think it was too dry. The book titled Deep Learning: From Curiosity To Mastery is much more approachable.
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Reviewed in the United States on May 22, 2026
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Amazon Customer
Battle Creek, US
★★★★★ 5
Comprehensive! The Bible of Deep Learning!
This book has by far surpassed my expectations! I have purchased many machine learning and deep neural network books in the past, but nothing has ever come close to this book! First of all, it is written by the fathers of Deep Learning, and is therefore an authority. Secondly, the book is broken into three parts: 1. A math overview and refresher. 2. Deep Learning applications and 3. Research in Deep Learning. I can't help but go through this book from front to back. It is a smooth read, and every sentence written is meaningful. These guys know their stuff! And after you read this book, YOU WILL ALSO know your stuff! If you feel daunted by the price, just remember, you get what you pay for! I'd say they could easily charge about $300+ for this book, but they are doing everyone a very kind favor by ONLY charging this reasonable amount. You get A LOT of bang for your buck with this purchase. I hesitated at first about buying this book because of the price, but I am soooooo happy that I did! Worth every penny! Look no further, get this book and start your Deep Learning journey!!
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Reviewed in the United States on July 14, 2017
M
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mackster
Dallas, US
★★★★★ 1
A rushed, poorly written guide of how the "experts" can't really explain what Deep Learning is
Format: Hardcover
This book, in every sense of the word, is rushed. I think the authors wanted to establish themselves as leaders of this young-ish field, but does so by sacrificing quality. It also shows that Deep Learning theory has been there for a long time, known by another name called Neural Networks. The interesting algorithms are of MLP, Back Propagation and the classical neural networks. The optimization methods such as Adam are the ones that are new and interesting, and the only ones worthy of in this book. So, essentially, what you get from this book is use A for X, B for Y and C for Z type of dry, un-intuitive, badly written waste of paper. As for the structure of the book, it's like an example of how not to structure a book. It has some linear algebra, probability at the start (not good enough, and confuses more people and wastes paper). Goes on to prove other algorithms such as PCA (yeah, ok!). Then, talks about how this architecture works for this and that architecture. So, yeah, if you really want to try out deep learning, don't buy this book. Set up Tensorflow/pytorch/ other library, run the tutorials, find an architecture for the problem you are interested in and start tweaking that. You will have far more fun and would have saved your money. The praise that this book gets is beyond me. Did Musk even read this book? I doubt it.
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Reviewed in the United States on May 15, 2018
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Stergios Papadimitriou
Waukegan, US
★★★★★ 5
The classic textbook on Deep Learning
Format: Hardcover
Deep Learning is the promising direction towards general purpose effective artificial intelligence. There is an explosion of fruitful research in recent years and a lot of applications pursued mainly from technology giants as Google, Amazon, etc. and outstanding research institutions. The book "Deep Learning " by Ian Goodfellow, Yoshua Bengio, Aaron Gourville, is an excellent piece of work. They manage to present rather difficult things in an understandable manner. The theoretical presentation is outstanding typical of "classic" books. Also, the book stays close to the practical applicability of all the methods and discusses applications extensively. There are a lot of other useful books on deep learning that follow a more practical approach by focusing on a particular deep learning software package, but this one book is certainly much more essential since it provides the required theoretical background in order to be able to do serious work on deep learning. I consider the book as "must have" for anyone that works on deep learning either in an academic or in an industrial environment.
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Reviewed in the United States on August 25, 2018
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Sabrina
Battle Creek, US
★★★★★ 5
100% Recommend
Format: Paperback
Invincible Compendium One completely lived up to the hype. From the very first chapter, I was hooked by the story, the action, and the character development. What starts off feeling like a classic superhero story quickly becomes something much deeper, darker, and way more emotional than expected. The artwork is incredible and the fight scenes are intense without feeling repetitive. Every character feels important and layered, especially Mark and Omni-Man. The pacing is excellent for such a massive collection, and it’s hard to put down once you start reading. If you’re a fan of superhero comics but want something with real stakes, shocking twists, and strong storytelling, this is absolutely worth reading. Easily one of the best graphic novels I’ve picked up in a long time.
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Reviewed in the United States on May 23, 2026

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