SKU: 86099693444

Extreme+ Brake System Rear 4262094GB

Sale price$2137.47 Regular price$2374.97
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Description

Extreme+ Brake System Rear 4262094GBFits Rear Ends w Ford 8" 9" Small Bearing Housing Ends, (5x5. 00"BC) Features: 1 Piece Monoblock, 6 Piston, 6S Caliper Manufactured in Phoenix, AZ CNC Machined from US Sourced 2618 Aluminum Forging Powder Coated Finish Stainless Steel Pistons, Abutments and Noise Suppression Clips Staggered Pistons to Minimize Uneven Pad Wear Dual Seals, Dust Weather & Pressure 2 Piece Slot, Drilled, Zinc Plate Rotor w Billet Aluminum Hat Specs: Axle Rear Axle Flange

Fits Rear Ends w/Ford 8"/9" Small Bearing Housing Ends, (5x5.00"BC)


Features:

  • 1-Piece Monoblock, 6-Piston, 6S Caliper Manufactured in Phoenix, AZ
  • CNC Machined from US Sourced 2618 Aluminum Forging
  • Powder Coated Finish
  • Stainless Steel Pistons, Abutments and Noise Suppression Clips
  • Staggered Pistons to Minimize Uneven Pad Wear
  • Dual Seals, Dust/Weather & Pressure
  • 2-Piece Slot, Drilled, Zinc-Plate Rotor w/Billet Aluminum Hat

Specs:

Axle Rear
Axle Flange Ford 8"/9" Small Bearing
Brand Baer Brakes
Caliper 6S
Caliper Color Grabber Blue
Disc Brake Caliper (Rear) Piston Quantity 6
Disc Brake Caliper (Rear) Type Fixed
Disc Brake Pad FMSI Number D1247
Disc Brake Rotor (Rear) Construction Vented
Disc Brake Rotor (Rear) Outside Diameter 14.000IN
Emission Code 6
Export Description Brake Components
Grade Type Performance
Hose Material Stainless Steel
Includes Park Brake Yes
Includes Park Brake Cables No
Lug Count 5 Lug
Min Wheel Dia (verify using template) 18IN
Product Line 14 Inch Extreme+
Product Type 14 Inch Extreme+ Rear Brake Kit
Prop 65 (C, R or CR) CR
Prop 65 - Long Label WARNING: This product can expose you to chemicals including Toluene Diisocyanate, and Nickel which are known to the State of California to cause cancer. For more information, visit www.P65Warnings.ca.gov
Prop 65 - Short Label WARNING: Cancer and Reproductive Harm. www.P65Warnings.ca.gov
Prop 65 Yes/No Yes
Rotor Thickness 1.250IN
Rotor Type 2-Piece
Surface Type Slotted, Drilled & Zinc Plated
System Notes Fits Ford 8"/9" small bearing housing ends
Template N085P
Title Extreme+ Brake System Rear
Wheel Lug/Bolt Pattern 5x5.00
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SKU: 86099693444

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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
Charlottesville, 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
West Palm Beach, 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
Natrona Heights, 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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3rd Act
Phoenix, US
★★★★★ 5
An Easy Read
Format: Paperback
A good narrative description of how the various systems work. Good for getting a conceptual understanding. No math to speak of, and if you want it, you can refer to the references cited, or your other favorite machine learning book.
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Reviewed in the United States on May 7, 2024

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