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Skunk2 Pro Series Mitsubishi Evo VIII/IX Black Series Intake ManifoldThe intake manifold solution street driven Evo VIII IX owners have been waiting for is here. Skunk2's Evo Pro Series Intake Manifold in its signature Black Series finish was designed with 'street enthusiasts' who utilize turbochargers as small as the factory unit in mind and want more power without sacrificing mid range performance. Skunk2's all new, cast aluminum Evo Pro Series Intake Manifoldwhich was tested and developed on the company's own Evo
The intake manifold solution street-driven Evo VIII-IX owners have been waiting for is here. Skunk2's Evo Pro Series Intake Manifold in its signature Black Series finish was designed with 'street enthusiasts' who utilize turbochargers as small as the factory unit in mind and want more power without sacrificing mid-range performance. Skunk2's all-new, cast-aluminum Evo Pro Series Intake Manifold—which was tested and developed on the company's own Evo Time Attack race car—is a direct-fit replacement and offers significant horsepower and torque gains without compromising mid-range power output. Conventional large-plenum, short-runner intake manifolds provide top-end power gains but suffer in the mid-range. Not Skunk2's. Its all-new Pro Series Intake Manifold features OEM-length runners with larger bores and a special tapered design as well as a larger, tapered plenum that together preserve mid-range power but increase and accelerate airflow to allow for significant top-end gains. Peak gains as high as 33+ whp have been realized when paired with Pro Series Throttle Bodies with positive results across the board, beginning as low as 3,200 rpm. Pro Series Intake Manifolds also feature thicker castings when compared to the OEM piece, which leaves plenty of room for porting, and each runner exit is machined and hand-finished to best match the cylinder head's ports. The Pro Series Intake Manifold's unique design increases wave scavenging effects at the engine's ideal operating range, which allow for a broad increase in usable power. Skunk2's Evo Pro Series Intake Manifold is a simple bolt-on affair. Unlike other intake manifolds, Skunk2's incorporates the factory configuration, leaving the throttle body in its original location, which means the original intercooler piping and hoses can be reused. Pro Series Intake Manifolds also include the necessary provisions for the Evo's brake booster line, MDP sensor, and vacuum accessories (EGR valve excluded)Shipping Notes
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4.5 ★★★★★
Based on 18 reviews
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Product Reviews
★★★★★ 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
★★★★★ 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
★★★★★ 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
★★★★★ 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
★★★★★ 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