SKU: 74515788037

Fabtech K7065DL 3 UCA SYS W/ DL 2.5 C/O RESI & RR LEAF PACK 05-14 TOY TACOMA 2WD/4

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Description

Fabtech K7065DL 3 UCA SYS W/ DL 2.5 C/O RESI & RR LEAF PACK 05-14 TOY TACOMA 2WD/4Obtain increased Wheel travel with a mild lift height with this heavy duty Upper Control Arm systems. The tubular Upper Control Arms feature 1. 25" OD, . 120" wall thick chromoly tube construction with 1" diameter Stainless Steel Uniballs that attach to the factory spindle without drilling. The replacement UCA's have been designed to work in conjunction with Fabtech's Dirt Logic 2. 5 Coilover shocks providing 10" of Wheel travel for a complete front

Obtain increased Wheel travel with a mild lift height with this heavy duty Upper Control Arm systems. The tubular Upper Control Arms feature 1.25" OD, .120" wall thick chromoly tube construction with 1" diameter Stainless Steel Uniballs that attach to the factory spindle without drilling. The replacement UCA's have been designed to work in conjunction with Fabtech's Dirt Logic 2.5 Coilover shocks providing 10" of Wheel travel for a complete front suspension system upgrade. A rear three leaf spring pack enhances the factory leaf springs by eliminating the stiff lower overload leaf. This allows for more flexibility and travel while enhancing the ride quality. Front stainless steel Dirt Logic 2.5 Coilovers with Eibach springs provide 10" of Wheel travel for aggressive offroad use. The rear Dirt Logic 2.25 shocks will also provide 10" of travel due the remote reservoir allowing for the full stroke of the shock.

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SKU: 74515788037

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MrGee
Lexington, US
★★★★★ 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.
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Reviewed in the United States on August 5, 2021
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R. Cote
Los Angeles, US
★★★★★ 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
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Rafael Azevedo Souza Costa
Belleville, US
★★★★★ 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
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Thomas
Fort Morgan, US
★★★★★ 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
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La Monte HP Yarroll
Dallas, US
★★★★★ 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.
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Reviewed in the United States on April 13, 2025

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