lavida plus damen trekking e bike 28 zoll 28 Zoll Damen E-Bike LS City Fahrrad MOTIVE TF 1.7 Trekking Bike BOSCH
SKU: 75095591045
lavida plus damen trekking e bike 28 zoll

lavida plus damen trekking e bike 28 zoll 28 Zoll Damen E-Bike LS City Fahrrad MOTIVE TF 1.7 Trekking Bike BOSCH

Sale price$23.96 Regular price$26.62
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Description

lavida plus damen trekking e bike 28 zoll 28 Zoll Damen E-Bike LS City Fahrrad MOTIVE TF 1.7 Trekking Bike BOSCH28" Damen E Bike LS City Fahrrad MOTIVE TF 1. 7 Trekking Bike BOSCH ACTIVE PLUS LINE Komfortables Damen E Bike fr Alltag & Freizeit Das MOTIVE TF 1. 7 Wave fr Damen verbindet modernes Design, hohen Fahrkomfort und leistungsstarke Technik. Ob fr den tglichen Weg zur Arbeit, entspannte Touren oder Fahrten durch die Stadt dieses Trekking E Bike bietet zuverlssige Untersttzung und ein angenehmes Fahrerlebnis. BOSCH ACTIVE LINE PLUS GEN 3 Motor Der

28" Damen E-Bike LS City Fahrrad MOTIVE TF 1.7 Trekking Bike BOSCH ACTIVE PLUS LINE 

Komfortables Damen E-Bike für Alltag & Freizeit

Das MOTIVE TF 1.7 Wave für Damen verbindet modernes Design, hohen Fahrkomfort und leistungsstarke Technik. Ob für den täglichen Weg zur Arbeit, entspannte Touren oder Fahrten durch die Stadt – dieses Trekking E-Bike bietet zuverlässige Unterstützung und ein angenehmes Fahrerlebnis.


BOSCH ACTIVE LINE PLUS GEN 3 Motor

Der leistungsstarke BOSCH ACTIVE LINE PLUS GEN 3 Motor sorgt für eine harmonische und kraftvolle Unterstützung bei jeder Fahrt. Dank der natürlichen Leistungsentfaltung fahren Sie komfortabel durch die Stadt und meistern auch leichte Steigungen oder längere Strecken mühelos.


BOSCH POWERPACK 400 Akku

Der BOSCH POWERPACK 400 Akku mit 400 Wh bietet eine zuverlässige Reichweite für Alltag und Freizeit. Der Akku ist elegant im Rahmen integriert, leicht entnehmbar und bequem aufladbar. Dadurch profitieren Sie von mehr Flexibilität und einer ausgewogenen Gewichtsverteilung.


RST Federgabel mit 80 mm Federweg

Die RST 29 BLAZE ML Federgabel mit 80 mm Federweg absorbiert Unebenheiten zuverlässig und sorgt für zusätzlichen Komfort auf Asphalt, Schotter oder Radwegen. So genießen Sie jederzeit ein ruhiges und stabiles Fahrgefühl.


ALHONGA HT474 4FINGER Bremsen

Die ALHONGA HT474 4FINGER Bremsen bieten eine sichere und kraftvolle Bremsleistung bei unterschiedlichen Wetterbedingungen. Die präzise Dosierung sorgt für maximale Kontrolle und Sicherheit im Straßenverkehr.


Stilvoll, sicher & alltagstauglich

Der komfortable Wave-Rahmen ermöglicht ein bequemes Auf- und Absteigen und macht das MOTIVE TF 1.7 zum idealen Damen E-Bike für Alltag, Freizeit und längere Touren.

Alle Airtracks E-Bikes mit Bosch- oder Shimano-Motoren verfügen über abnehmbare und abschließbare Akkus. Diese lassen sich einfach entnehmen, separat laden und bieten zusätzlichen Schutz vor Diebstahl.


Highlights
  • 28 Zoll Damen Trekking E-Bike
  • BOSCH ACTIVE LINE PLUS GEN 3 Motor
  • BOSCH POWERPACK 400 Wh Akku
  • RST Federgabel mit 80 mm Federweg
  • ALHONGA HT474 4FINGER Bremsen
  • Komfortabler Wave-Rahmen
  • Abnehmbarer & abschließbarer Akku

Alle Airtracks E-Bikes mit Bosch- oder Shimano-Motoren sind mit abnehmbaren und abschließbaren Batterien ausgestattet.
Diese bieten mehr Komfort und Sicherheit als fest verbaute Akkus, da sie einfach vom Fahrrad entfernt, separat aufgeladen und vor Diebstahl geschützt werden können.

Dieses Fahrrad wird zu 98 % fertig montiert geliefert. Die fahrfertige Endmontage von Lenker und Pedale ist von einer fachkundigen Person durchzuführen.

GRÖßENEMPFEHLUNG

Rahmengröße Empfohlene Körpergröße
46 cm 165–175 cm
50 cm 175–185 cm
54 cm 185–195 cm
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SKU: 75095591045

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4.1 ★★★★★
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Product Reviews
N
Nader
Lexington, US
★★★★★ 1
Light on substance and heavy on flaws
Format: Paperback
The book has a great list of topics, but fails to provide much substance any of them. Most of the provided code is just comments that avoid the actual crux of the issues being discussed. (e.g. #implement the logic to validate XYZ - while the whole point of this chapter is teach how the heck we validate XYZ!) Some parts are plain wrong, for example the part on Graph based RAG is fundamentally flawed as it assumes the text embedding and the graph embedding are in the same latent space. (This is one of many more examples). Seems like the book was rushed, and the author has limited hands on experience (if any). At least we know based on the amount of flaws that it was not written by an LLM
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on December 31, 2025
N
noam barkay
Phoenix, US
★★★★★ 5
Excellent book to truly understand LLM design patterns
Format: Paperback
I just finished reviewing Ken Huang's pocket book on LLM Design Patterns, and WOW what an amazing resource! This book is excellent if you want to truly understand how to create and enhance intelligent AI language models, all that in your pocket! Ken makes the difficult things seem surprisingly easy, and that's the real MAGIC. - How to prepare your data for training by making it extremely clean. Developing the brains: the practical aspects of training, optimizing, and maintaining your models. - Learn amazing prompting techniques (such as Chain-of-Thought and Tree-of-Thoughts) to improve your AI's reasoning and problem-solving abilities. Learn everything there is to know about RAGs so that your LLM can incorporate outside expertise. - It also delves into creating "agentic" AI that is capable of action and planning (not only simple plan and execute but also enhanced techniques like ReWoo!) Really, this feels like a useful toolkit, so Ken thank you for that resource Thanks, Idan Habler
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on June 9, 2025
R
Ryan Meyer
Cuba, US
★★★★★ 3
A Broad Overview, But Light on Modern Fine-Tuning
Format: Paperback
I'm currently really interested in fine-tuning LLMs and recently completed my first LoRA-based fine-tuning on a quantized model. I came to this book looking for more detail on fine-tuning. While it touches on the topic, I found the content didn’t quite align with the current state of the field in 2025. Techniques like LoRA, QLoRA, and PEFT weren’t really covered, and the material leaned more toward what I think are older or lower level approaches. That made it harder to connect with what I’m actually working on. That said, when I shifted to other chapters — like the sections on prompt engineering techniques such as Chain of Thought (CoT) and Tree of Thought (ToT) — I found more value. These sections were clearer, and I picked up a few practical insights, like using few-shot examples that walk through the CoT reasoning process. That’s not something I’ve tried before, and I can see how it might help smaller models that struggle with any type of reasoning tasks. Overall, the book feels more like a broad overview of all LLM concepts. For someone exploring many topics across the LLM ecosystem, it offers a wide-ranging introduction. But for readers like me who are actively trying to learn and apply techniques like fine-tuning and quantization, it may leave you wanting up-to-date guidance.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on August 10, 2025
V
Vineeth Sai
Dallas, US
★★★★★ 5
Great foundation read for security!
Format: Paperback
This book is a great read! It builds a strong foundation and I would highly recommend it for builders who are interetsed in building on LLMs and ensuring everything is secure. Security is super important and this book does it justice!
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on June 27, 2025
C
Verified Purchase
CL
Houston, US
★★★★★ 5
Loved it
Format: Paperback
I’ve easily read dozens of tech books. I liked this one a lot. Sure, there were boring parts, but most of it was engaging, especially on dry subjects. I previously read “How AI Works” and found this more informative and way more enjoyable. I got through the 700 pages in about 5 weeks while also learning about probability and linear algebra from other books and online sources. I’d love to read something more advanced by the author, maybe getting into more modern applications. I feel more comfortable with the subject and feel I am now ready to conquer more advanced texts. I initially picked this up to give me some background before reading “How to Build a LLM (from scratch)”. I’ve ordered an intermediary Deep Learning with Python book as well, but wouldn’t mind a more advanced theory book to accompany these books. I’ll definitely be rereading sections of this book to further familiarize myself with topics like backpropagation. Highly recommend if you’re looking for a gentle, but broad introduction to the topic.
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Reviewed in the United States on November 14, 2025

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