D2031 - Tarcze hamulcowe Premium Gładkie (Para) EBC Brakes FORD | Focus (Mk3) | Focus (Mk4) | FORD | Focus
SKU: 76744880409

D2031 - Tarcze hamulcowe Premium Gładkie (Para) EBC Brakes FORD | Focus (Mk3) | Focus (Mk4) | FORD | Focus

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Description

D2031 - Tarcze hamulcowe Premium Gładkie (Para) EBC Brakes FORD | Focus (Mk3) | Focus (Mk4) | FORD | FocusTarcze hamulcowe samochodowe GADKIE, to wysokiej jakoci zamiennik seryjnych tarcz hamulcowych, ktrych wytrzymao oraz skuteczno hamowania jest duo lepsza od seryjnych tarcz. Tarcze s produkowane w Wielkiej Brytanii oraz w Niemczech (obecnie produkcja poszerzona zostaa o kolejne kraje takie jak Japonia i Wochy). Specjalnie opracowana technologia oraz dobr komponentw, pozwalaj na bezproblemowe oraz dugie uytkowanie tarcz. Ich wytrzymao powoduje e, mog



Tarcze hamulcowe samochodowe GŁADKIE, to wysokiej jakości zamiennik seryjnych tarcz hamulcowych, których wytrzymałość oraz skuteczność hamowania jest dużo lepsza od seryjnych tarcz. Tarcze są produkowane w Wielkiej Brytanii oraz w Niemczech (obecnie produkcja poszerzona została o kolejne kraje takie jak Japonia i Włochy). Specjalnie opracowana technologia oraz dobór komponentów, pozwalają na bezproblemowe oraz długie użytkowanie tarcz. Ich wytrzymałość powoduje że, mogą współpracować ze wszystkimi klockami EBC Brakes, włącznie z klockami serii RED STUFF (czerwonymi), YELLOW (żółtymi) oraz BLUE (niebieskimi).

DANE TECHICZNE
  • Typ: Gładkie
  • Pełne/Wentylowane: Pełne
  • Ilość otworów: 5
  • Średnica (mm): 302
  • Wysokość (mm): 41
  • Grubość (mm): 11
  • Minimalna grubość (mm): 9
  • Zastosowanie na oś: Tył
ZASTOSOWANIE

Marka Model Silnik Wartość Moc (KM) Rocznik
FORD FOCUS (MK3) 2.3 TURBO RS 350 2016-2018
FORD FOCUS (MK4) 1.0 TURBO 125 2018-
FORD FOCUS (MK4) 1.5 TD 120 2018-
FORD FOCUS (MK4) 1.5 TURBO 150 2018-
FORD FOCUS (MK4) 1.5 TURBO 180 2018-
FORD FOCUS (MK4) 2.0 TD 150 2018-
FORD FOCUS (MK4) 2.0 TD ST 190 2019-
FORD FOCUS (MK4) 2.3 TURBO ST 280 2019-

Rzeczywisty wygląd towaru może różnić się od tego, który widnieje na zdjęciach.

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SKU: 76744880409

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4.6 ★★★★★
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Verified Purchase
David Escobar
Chelsea, US
★★★★★ 1
Nothing new
Format: Audiobook
There nothing new in this book you will defiantly find this content in any leadership book
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on November 16, 2019
F
Verified Purchase
Filipe Fernandes
Houston, US
★★★★★ 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
E
Verified Purchase
Eddwin Paz
Birmingham, US
★★★★★ 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
B
Verified Purchase
B. Black
Belleville, US
★★★★★ 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
J
Joe Faith
Omaha, US
★★★★★ 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

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