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Description
ICON 2005+ Toyota Tacoma 4WD 1.5-3in Rear 2.0 Series Aluminum Shocks NRICON Vehicle Specific (V. S.) 2. 0 Aluminum Series shock absorbers are the ultimate in cost effective upgrades, specifically tailored by ICON engineers for your application. The V. S. 2. 0 Aluminum Series shocks are a high quality upgrade for the everyday street driver and weekend warrior looking for improved on and off road performance. Like all ICON shock absorbers, V. S. 2. 0 Aluminum Series shocks are 100% rebuildable and 100% revalveable. For
ICON Vehicle Specific (V.S.) 2.0 Aluminum Series shock absorbers are the ultimate in cost effective upgrades, specifically tailored by ICON engineers for your application. The V.S. 2.0 Aluminum Series shocks are a high quality upgrade for the everyday street driver and weekend warrior looking for improved on and off-road performance. Like all ICON shock absorbers, V.S. 2.0 Aluminum Series shocks are 100% rebuildable and 100% revalveable. For those using their vehicle in extreme off road situations, consider the ICON V.S. 2.5 Series shock to handle extra abuse and punishment your suspension will need to endure.This Part Fits:
| Year | Make | Model | Submodel |
|---|---|---|---|
| 2005-2015 | Toyota | Tacoma | Base |
| 2016-2023 | Toyota | Tacoma | Limited |
| 2005-2015 | Toyota | Tacoma | Pre Runner |
| 2016-2023 | Toyota | Tacoma | SR |
| 2016-2023 | Toyota | Tacoma | SR5 |
| 2021 | Toyota | Tacoma | Trail |
| 2023 | Toyota | Tacoma | Trail Special Edition |
| 2016-2023 | Toyota | Tacoma | TRD Off-Road |
| 2015,2017-2023 | Toyota | Tacoma | TRD Pro |
| 2016-2023 | Toyota | Tacoma | TRD Sport |
| 2005-2013 | Toyota | Tacoma | X-Runner |
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4.8 ★★★★★
Based on 18 reviews
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Product Reviews
★★★★★ 5
An enjoyable, and seriously excellent, path to understanding Deep Learning...
Format: Paperback
Deep Learning is changing our world. If you want to understand more, this is a great place to start. Andrew Glassner is a talented explainer - I took his short course on Deep Learning and learned so much, but also came away impressed at how well he can make complex material so clear and engaging. And this book is jammed packed with insights, visuals, and clear explanations. The author has a playful, sometimes quirky style that shines through, which gives this tour a lot of personality as well as information. Very enjoyable reading - I felt like he captured all that was good about his course (and then some) and bottled it up in this book. There is a lot more material here than in that course, and it is well laid-out and organized so that it is easy to roam around and come back to review the pieces that matter to you.
Even if you plan to go to on to be a world-class Deep Learning engineer or mathematician, you have to start by understanding the concepts. And this book does a great job of presenting all the core ideas in a way that makes them clear and memorable.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on August 5, 2021
★★★★★ 5
Before GPT can chat, it has to learn.
Format: Paperback
One of the most comprehensive guides to AI and deep learning available. All concepts covered clearly and concisely with illustrations. Complex concepts are broken down into understandable terms. Even though ML and AI require some complex math, you won’t need it to get idea of what’s going on inside the computer’s “brain”.
I use this as a reference when teaching AI concepts and preparing presentations.
I highly recommend it
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Reviewed in the United States on April 5, 2025
★★★★★ 5
Great examples and practical explanations
Format: Paperback
Excellent book. Highly recommend
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Reviewed in the United States on May 19, 2025
★★★★★ 5
Great for intuitive understanding
Format: Paperback
Amazing book. Great examples and diagrams. If you're looking to get an intuitive grasp of deep learning, look no further. If you're an engineer looking to apply it, I would recommend pairing this with one of the more technical canonical texts and a programming focused book.
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Reviewed in the United States on May 4, 2024
★★★★★ 5
Taught me backpropagation
Format: Paperback
I'm finding this book a great reference to supplement Syracuse IST 691 Deep Learning in Practice. In particular, its explanation of backpropagation is the clearest I have found yet, and that even includes 3 Blue 1 Brown, which always does excellent explanations.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on April 13, 2025
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