SKU: 9711715671

ICON K73063T 1.5-3.5" Stage 3 Suspension System With Tubular UCA

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Description

ICON K73063T 1.5-3.5" Stage 3 Suspension System With Tubular UCAThe Icon K73063T 1. 5 3. 5" Stage 3 Suspension System With Tubular UCA are designed to dramatically increase on and off road ride quality of your 2019 2023 GM Silverado Sierra 1500 2WD 4WD (See Application Notes). Icon engineers' primary focus is to increase wheel travel and damping ability, which translates into outstanding vehicle control and ride quality both on and off road. With wheel travel and ride quality in mind, Icon engineers researched

The Icon K73063T 1.5-3.5" Stage 3 Suspension System With Tubular UCA are designed to dramatically increase on and off-road ride quality of your 2019-2023 GM Silverado/Sierra 1500 2WD/4WD (See Application Notes). Icon engineers' primary focus is to increase wheel travel and damping ability, which translates into outstanding vehicle control and ride quality both on and off-road. With wheel travel and ride quality in mind, Icon engineers researched each component of the GM platform's suspension and addressed any areas where performance could be extracted. The Stage 3 system includes vehicle-specific tuned 2.5 Series coilover shocks featuring a remote reservoir for exceptional cooling properties and Icon-engineered Eibach coil springs for superior vehicle "feel" through the range of travel. These coilovers are also height adjustable from 1.5-3.5" allowing the use of larger, more aggressive wheel and tire combinations. Icon 2.5 Aluminum Series piggyback reservoir rear shocks utilize a vehicle-specific valving that balances the performance of the truck from front to rear. The Icon Vehicle Dynamics 2019-2023 GM Silverado/Sierra 1500 Stage 3 suspension system is an excellent choice for those drivers looking to enhance the capabilities of their pickup on the road as well as in the dirt.

Features:
  • Adjustable Coilovers Provide 1.5-3.5" Of Front Lift Height
  • Increased Lift Height Allows For Fitment Of Larger And More Aggressive Tires
  • Fits 2WD/4WD Applications
  • Up To 35% Increase In Front Wheel Travel Over Stock
  • Icon Shocks Feature Vehicle Specific Tune For Superior Performance And Ride Quality
  • 2.5 Series Coilover Shocks Feature Corrosion Resistant CAD Plated Shock Body With 7/8" Shaft
  • 2.5 Aluminum Series Rear Shocks Feature One-Piece Impact Extruded Aluminum Cylinders For Excellent Corrosion Resistance And Consistent Finish
  • 7.5" Aluminum Reservoirs Provide Generous Oil And Nitrogen Volume For Consistent Damping As Shock Temperature Increases
  • FK Rod End Bearings Provide Extended Longevity And Minimal Deflection
  • Shocks Are Fully Rebuildable And Re-Valvable
  • Icon Upper Control Arms Allow For Additional Wheel Travel (When Paired With Extended Travel Coilovers) While Improving Suspension Geometry For Predictable Handling
  • Patented Delta Joint (U.S. Pat. 10,731,700) Combines The Durability And Weather Resistance Of A Ball Joint With The Performance Characteristics Of A Uni-ball
  • Direct Bolt-In Design Makes For A Simple And Straightforward Installation
  • Lifetime Guarantee Against Icon Fabricated Component Breakage Or Manufacturer Defect



Notes:
OEM Wheels & Tires Fitment: Yes
Recommended Aftermarket Wheels: Icon Alloys | 17x8.5" W/ 4.75" Backspace / 0mm Offset
Recommended Aftermarket Wheels: Icon Alloys | 18x9" W/ 5.00" Backspace / 0mm Offset
Recommended Aftermarket Wheels: Icon Alloys | 20x9" W/ 5.00" Backspace / 0mm Offset
Recommended Aftermarket Tires (Silverado): 35"X12.50" (Minor Fender Trimming And Modifications May Be Required)
Recommended Aftermarket Tires (Sierra): 34"X12.00" (Minor Fender Trimming And Modifications May Be Required)
Application Note #18: These Systems Are To Be Used With Aftermarket Upper Control Arms Only
Application Note #48: Slight Modifications To Factory Shock Mounts May Be Required
Application Note #55: Shocks Are Fully Serviceable. Coilover Heights Indicated Are For A Stock Equipped Vehicle
Application Note #110: Minor Trimming Required For Recommended Tire Size
Tech Note: Not Compatible With Models Equipped With Adaptive Ride Control (Arc)
Tech Note: Not Compatible With Models Equipped With 4-Cylinder Engine
Tech Note: Not Compatible With Silverado 1500 ZR2 Or Sierra 1500 AT4X Sub-Models
Tech Note: Models Equipped With Duramax 6-Cylinder Diesel Engine Will Have Lift Height Adjustment Range Reduced By Approximately .5"
Tech Note: Included Rear Shocks Are Compatible With 0-2" Of Rear Lift On Most Models. Rear Shocks Are Not Recommended With Any Additional Rear Lift On Silverado 1500 Trail Boss And Sierra 1500 At4.
Tech Note: Chevrolet Silverado Trail Boss And Gmc Sierra 1500 At4 Lift Height Range 0-1.5" Over Stock
Tech Note: Recommend Replacing OE Rear Blocks On Silverado 1500 Trail Boss And Sierra 1500 At4 Models With 1" Rear Blocks If Level Stance Is Desired. See Icon Part Numbers 51001 And 52050.
Tech Note: Not Compatible With Models Equipped With Torsion Bar Front Springs
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SKU: 9711715671

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4.8 ★★★★★
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Verified Purchase
Amazon Customer
Draper, US
★★★★★ 4
Just learning it
Format: Paperback
Nice learning book just have to finish it
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on December 10, 2025
K
Verified Purchase
Kindle Customer
West Palm Beach, US
★★★★★ 5
Very useful book
Format: Paperback
I use it for the machine learning class I teach.
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Reviewed in the United States on May 3, 2026
T
Verified Purchase
Tommy Jonsson
Alexandria, US
★★★★★ 5
Cover many areas in detail and recommendations for more to read for what's outside
Format: Paperback
Good book!
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on May 4, 2026
M
Verified Purchase
Moses Kayanda
Draper, US
★★★★★ 5
One of the best machine learning books...
Format: Paperback, Format: Paperback
Machine Learning can often be intimidating whether you are starting out or already a practitioner. It is easy to get stuck on one concept, walk away frustrated, or just copy that code you find on StackOverflow without really understanding what it does. What the authors of this book, Machine Learning with PyTorch and Scikit-Learn, have managed to do is to keep the reader engaged giving a deeper illustration as to how the concepts work. In this book, you get practical code examples, a detailed explanation of how the various library tools work, and exposure to the mathematical concepts behind machine learning algorithms. In addition, what I like about the book unlike many machine learning books is that the authors have managed to intuitively explain how each algorithm works, how to use them, and the mistake you need to avoid. I have not read a Machine Learning book that better explains Transformers as this one does. The authors have managed to give a detailed dive into this model architecture through well-explained codes and illustrations. As a reader, you walk away having intuitively grasped the concepts of attention and self-attention in ways that will make this crucial NLP architecture clear. You get exposed to pre-trained models from HuggingFace library which really helps to have that hands-on experience working with large datasets. As they have done throughout the book, the authors have broken down those complex mathematical operations into simple explanations that are easy to follow. What I generally like about the book is how it seamlessly connects all the chapters, not throwing off the reader. There are numerous external resources quoted throughout the book. This helps spark that curiosity to dig deeper. In addition, you get introduced to PyTorch, getting exposed to all those sophisticated libraries that help the reader learn how to maximize their compute power. I would say it is not intimidating at all even if you have not used PyTorch before. I would recommend this book to anybody seeking a textbook that is both easy to read and modern in its content. If were to rate the book I will give it a 10/10 as it really applies to both beginners and experienced practitioners, covers all the concepts one needs to apply in their operations, and acts as a quick reference.
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Reviewed in the United States on March 1, 2022
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Verified Purchase
Gabe Rigall
Grantham, US
★★★★★ 5
Thorough Primer for Machine Learning and PyTorch
Format: Paperback
BLUF: A thorough primer for machine learning enthusiasts with plenty of theory to underscore its many practical examples. A definite must-have for anyone looking to add PyTorch to their machine learning tool belt. PROS: - Extremely thorough (if not comprehensive). I really appreciate that this book doesn't just thrust one into building models with PyTorch. It starts at the "beginning" and provides examples, theory, additional resources, and citations along the way. - Theory. Those whose calculus and linear algebra courses ended many years ago will appreciate (if not remember exactly) the mathematical theory and notation that accompanies almost every paragraph. This book gives one the opportunity to "dig deeper" or stay in the shallows until the notation stops. - Python. Rather than simply utilizing Scikit-Learn to illustrate concepts and introduce models, this book contains many sections where models (such as a Perceptron) are coded from the ground up so the reader can fully understand the underlying mechanics. Python enthusiasts will nerd out. Parents of small children might want to skip a few pages. - Graphs, charts, and graphics. There are plenty of places where a drier text might have foregone the use of graphs. This text does not. It does however refrain from overusing them. - PyTorch. This should be obvious from the title, but this text prioritizes PyTorch instead of TensorFlow. This is especially helpful for those looking for an alternative to Keras and TensorFlow as the PyTorch API is very user-friendly. CONS: - Almost too much code. This isn't a true "con" but anyone wanting to emulate or follow along with the examples would do well to get the digital edition so they can copy and paste. - Length and complexity. Anyone hoping for a "quick read" or a "quick start guide" will be disappointed. This book hovers somewhere between an undergraduate primer and a graduate-level text for length and readability. This is not to say that it's difficult to read, merely that there are other "quick start" / "practical" texts out there that cater more to a lay audience.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on February 26, 2022

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