SKU: 30430810354

GPP RS Race Exhaust for FR-S/BRZ 2012-16

$241.54 $268.38
Save 10%
No.2 Bestseller on sm10m.ch >

Pay in installments of $67.09 with ShopPay, AfterPay and Klarna

Shipping Estimate
USA
  • USA
  • CAN

Ships within 48 hours · Estimated delivery Sep 25 - Sep 30

Promo Codes Available:

For Your Every Summer RSVP, with Code: SUMMER15

Description

GPP RS Race Exhaust for FR-S/BRZ 2012-16GReddy Performance Products RS Race Exhaust The GPP RS Race for the 2012 16 Scion FR S & Subaru BRZ is our most aggressive system we offer for the ZN6 chassis. The RS Race is ideally suited for turbocharged, race applications (or customers who want an aggressive sounding exhaust), which require less sound suppression and maximum flow. This light weight, single sided, full stainless steel 3. 0 (76mm) cat back RS Race exhaust exits the (left) driver

GReddy Performance Products RS-Race Exhaust

The GPP RS-Race for the 2012-16 Scion FR-S & Subaru BRZ is our most aggressive system we offer for the ZN6 chassis. The RS-Race is ideally suited for turbocharged, race applications (or customers who want an aggressive sounding exhaust), which require less sound suppression and maximum flow. This light-weight, single-sided, full stainless-steel 3.0” (76mm) cat-back RS-Race exhaust exits the (left) driver-side and has no pre-resonator. Even with the cost-effective price point on the RS-Race, quality materials, construction and craftsmanship is not compromised. For extra customization, the RS-Race Tri-bolt tip allows for installation of optional RS Tip Silencers, various tip lengths and styles in both stainless steel and genuine Titanium.

* Optional Tip Silencer : 51mm / 43mm

* Optional Titanium Tip (Burnt Finish) : L120 / L150 / L170

Chassis: ZN6
Engine: 4U-GSE (FA20)
Type: Cat-back exhaust

Number of pieces: 2pcs
Piping: 76mm (3.0")
Tip: 115 mm (4.5") x L170mm (6.7")
Gasket(s): 3" oval (qty: TBA included) replacement

Notes: replace factory doughnut-gasket and spring bolts for mid-pipe, with provided composite gasket and M8 nuts and bolts.


Weight: 17.6 lbs (Stock weight 39 lbs)
Sound level: 102 dB(a) *without optional silencer

HP: TBA hp
TRQ: TBA ft-lbs

*Data collected on stock vehicle *Retains catalytic convertor, front pipe
*TBA = To Be Announced

NOTE: From 2017-on the Toyota 86 and Subaru BRZ came with a slight change in the factory front "over-pipe" this change results in a need for a different position of the mid-pipe on many GReddy exhaust styles for the 2017-on "Kouki" models. To accomidate this change, GReddy now offers two models of each Evolution GT, Revolution GT, RS-RACE and RS-Ti system, one system for the 2012-2016 FRS/BRZ and another revised system for the 2017-on 86/BRZ.

Shipping Notes
  • Free Standard Shipping on $100+ Orders to the USA.
  • Except Preorder products are shipped in 48 hours.
  • Delivery to the USA:
  1. Standard Shipping : 3-10 business days
  • If time is of the essence, please consider selecting expedited delivery for faster service.
Exchange/Return Notes
  • We offer a 30-day return/exchange service after receiving.
  • Final sale items are not eligible for returns or exchanges.
  • To process your return/exchange, please contact us at [email protected]
  • Please click here for more details>>> Return & Exchange Policy
SKU: 30430810354

Discover Niche Categories That Outsell

Top-Converting Item to Boost Your Average Order

4.3 ★★★★★
Based on 26 reviews
Sort
Highest Rating
Newest First
Oldest First
Product Reviews
W
Verified Purchase
William P Ross
West Palm Beach, US
★★★★★ 5
Comprehensive Look At An Incredibly Complex Topic
Format: Hardcover
Deep Learning is an advanced book with great explanations and details. There is a heavy math focus with the book's beginning chapters detailing the necessary linear algebra and probability that one will need to understand deep learning. I liked that the author's chose to cover only the parts of these subjects which are relevant to deep learning. There are many interesting philosophical sections in the book as well. Just about when I was feeling overwhelmed with the complexity of the mathematics the authors take a step back and cover the foundations of deep learning such as borrowing concepts from human learning. There was an interesting dicussion about the early studies done on the vision of cat's and monkey's in the 1970s. The text covers the entire history of deep learning and the bibliography is hundreds of sources. It is clear this is the most comprehensive text available about deep learning. For anybody interested in this topic this book is a mandatory read. There are sections about machine learning as well, which makes sense because deep learning is a subset of machine learning. These sections focused on the machine learning concepts which are most relevant to deep learning. The book was well organized and divided into three parts which cover mathematics related to deep learning, typical deep learning techniques, and then more experiment learning techniques. Often the author's state when a technique works well or when it does not, and which types of data works best for the technique. Just a warning, the math in this book is highly complex. It requires a lot of work to go through this book, but the effort will be well rewarded.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on March 15, 2017
A
Verified Purchase
Adam
Phoenix, 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.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on May 22, 2026
A
Verified Purchase
Amazon Customer
Fort Morgan, 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!!
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on July 14, 2017
M
Verified Purchase
mackster
Battle Creek, 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.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on May 15, 2018
S
Verified Purchase
Stergios Papadimitriou
Port Orchard, 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.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on August 25, 2018

recommand products

PIRANHA DIAMONDS 856-016F (25/PK)
65.44
Keune Care Confident Curl Leave-In Curly
22.90
WHITE STONES FG CN1 (12/PK)
16.95
BENDA MICRO APPLICATORS (576/BX)
73.51
NEO BUR #245 FG (50/PK)
98.60