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Description
Pro+ Brake System Rear 4262149HOFits Rear Ends w Ford 9" Torino (Late Big) Bearing Housing Ends, (5x4. 5", 5x4. 75"BC) Features: 2 Piece, 6 Piston, 6P Caliper Manufactured in Phoenix, AZ CNC Machined from US Sourced Forged or Billet Aluminum 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
Fits Rear Ends w/Ford 9" Torino (Late Big) Bearing Housing Ends, (5x4.5", 5x4.75"BC)
Features:
- 2-Piece, 6-Piston, 6P Caliper Manufactured in Phoenix, AZ
- CNC Machined from US Sourced Forged or Billet Aluminum
- 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 9" Torino/Late Big Bearing |
| Brand | Baer Brakes |
| Caliper | 6P |
| Caliper Color | Hugger Orange |
| Disc Brake Caliper (Rear) Piston Quantity | 6 |
| Disc Brake Caliper (Rear) Type | Fixed |
| Disc Brake Pad FMSI Number | D0731 |
| Disc Brake Rotor (Rear) Construction | Vented |
| Disc Brake Rotor (Rear) Outside Diameter | 13.000IN |
| 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) | 17IN |
| Product Line | 13 Inch Pro+ |
| Product Type | 13 Inch Pro+ 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 | 1.100IN |
| Rotor Type | 2-Piece |
| Surface Type | Slotted, Drilled & Zinc Plated |
| System Notes | Designed to be used with Ford 9" Torino(aka late big/new style big Ford) bearing housing ends |
| Template | Q082H |
| Title | Pro+ Brake System Rear |
| Wheel Lug/Bolt Pattern | 5x4.50/5x4.75 |
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4.1 ★★★★★
Based on 2251 reviews
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Product Reviews
★★★★★ 1
Nothing new
Format: Audiobook
There nothing new in this book you will defiantly find this content in any leadership book
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Reviewed in the United States on November 16, 2019
★★★★★ 5
Great book
Format: Paperback
Love the fact you put examples in python and javascript.
Great book.
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Reviewed in the United States on June 10, 2025
★★★★★ 5
proper documentation from langchain
Format: Paperback
Liked the book. But Still missing Human in the loop.
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Reviewed in the United States on April 19, 2025
★★★★★ 3
Already outdated
Format: Paperback
Concepts are sound but the code in this book is already obsolete
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Reviewed in the United States on August 5, 2025
★★★★★ 5
Unlocking Practical AI: A Developer’s Guide to Building with LLMs and LangChain
Format: Paperback
If you're a developer eager to move beyond LLM experimentation and build robust, context-aware AI applications, this book offers both inspiration and practical guidance. The authors open with a clear passion for the transformative potential of large language models (LLMs) and LangChain, framing these technologies as not just enhancements to the developer’s toolkit, but as gateways to new kinds of “thing-building” superpowers. This sense of possibility is grounded in step-by-step instruction, making the book approachable for those with Python or JavaScript backgrounds who may be new to the world of production-grade AI agents.
What stands out is the book’s careful scaffolding: starting with foundational concepts like prompt-based programming and progressing to advanced capabilities such as retrieval-augmented generation, agent planning, and tool integration. Each stage is contextualized with real-world use cases, like customizing chatbots to interact with your own documents, personalizing user experiences through memory, and deploying to production with reliability and security in mind. The focus on chain-of-thought reasoning and LangGraph’s agent architecture demonstrates the authors’ awareness of the current state of AI, where context and planning are just as important as raw language ability.
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Reviewed in the United States on July 17, 2025