SKU: 51172977559

WILD M20 - Diamond Carbon View (Matt)/Mars Red (Gloss)

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Description

WILD M20 - Diamond Carbon View (Matt)/Mars Red (Gloss)The Yes Machine Das Wild ist ein Bike, bei dem wir keine Kompromisse gemacht haben. Es ist leicht und vollumfnglich optimiert und verlsst unsere Werkshallen einsatzbereit mit dem neuesten Bosch Motor und wettkampffhiger Ausstattung. Mit 170 mm Federweg vorn und hinten und einer Geometrie, die auf Tempo ausgelegt ist, weit du, dass es egal ist, welche Herausforderungen sich ihm stellen, das Wild ist bereit, sie zu meistern. Neues Integriertes Display

The Yes Machine
Das Wild ist ein Bike, bei dem wir keine Kompromisse gemacht haben. Es ist leicht und vollumfänglich optimiert und verlässt unsere Werkshallen einsatzbereit mit dem neuesten Bosch-Motor und wettkampffähiger Ausstattung. Mit 170 mm Federweg vorn und hinten und einer Geometrie, die auf Tempo ausgelegt ist, weißt du, dass es egal ist, welche Herausforderungen sich ihm stellen, das Wild ist bereit, sie zu meistern.

Neues Integriertes Display
Das neue Kiox 400C Display ist nahtlos in den Rahmen integriert und vor Stößen und Schlägen geschützt. Es verfügt über einen USB-C Ladeanschluss, anpassbare Anzeige Layouts und verschiedene Navigationsfunktionen.

170 mm Gravityorientierter Federweg
Das Wild bietet von und hinten 170 mm Federweg dank der maßgeschneiderten Fox Float-X oder Float-X2 Federelemente sowie der Fox 38 Gabel.

Modulares Akku System
Das Wild kommt standardmäßig mit einem 600 Wh Akku. Dieser leichtere Akku bietet ultimativ gutes Handling. Wer länger unterwegs sein möchte, wählt den 750 Wh Akku und den 250 Wh Range Extender als Optionen über MyO aus.

Bosch CX Performance Motor
Der 100 Nm Motor von Bosch mit seiner unendlichen Power und kontrollierten Reaktion muss nicht vorgestellt werden. Der verbesserte Motor erlaubt noch präzisere Kontrolle, er ist leiser und leichter und sorgt für weniger Tretwiderstand.

OMR Carbon
Dank hochfester Hochmodul Fasern und moderner Carbon Verarbeitungstechniken konnten wir weniger Carbon verwenden, ohne dass Stabilität und Steifigkeit darunter leiden.


Ausstattung:
Rahmen: Orbea Wild OMR 2025, 29" wheels, Concentric Boost 12x148
Dämpfer: Fox Float X Performance Trunnion 2-Pos Evol LV custom tune 205x65mm
Gabel: RockShox ZEB Base-A2 DebonAir+ 170 E-MTB specific 15X110 Boost
Lenker: OC Mountain Control MC30, Rise20, Width 800
Vorbau: OC Mountain Control MC20, 0º
Computer Mount: OC Computer Mount CM-05, Garmin/Sigma
Steuersatz: Alloy 1-1/2", Black Oxidated Bearing
Motor: Bosch Performance Line CX BDU3843
Akku: Bosch Powertube 750Wh Horizontal BBP3770
Display: Bosch System Controller BRC3100
Bedieneinheit: Bosch Mini Remote BRC3300
Ladegerät: Bosch Charger 4A (230V) BPC3400
Kurbel: e*thirteen Helix Core
Kettenblatt: e*thirteen e*spec Direct Mount 34T Boost
Kettenführung: e*thirteen Plus Bosch CX Gen4 CL 55 32-36t
Kassette: Shimano CS-M7100 10-51t 12-Speed
Kette: Shimano M6100
Schalthebel: Shimano Deore M6100 I-Spec EV
Schaltwerk: Shimano SLX M7100 SGS Shadow Plus
Bremsen: Shimano MT420 Hydraulic Disc
Bremsscheiben: Galfer Wave Rotors 203mm front / 203mm rear
Laufräder: Race Face AR 30c Tubeless Ready
Reifen: Maxxis Assegai 2.50" 60TPI 3CG/EXO+/TR MaxxGrip, Maxxis Minion 2.40" 120 TPI 3CT/DD/TR MaxxTerra
Sattel: Fizik Aidon 208x145mm manganese rail
Sattelstütze: OC Mountain Control MC22, 31.6mm, Dropper
Sattelstütz-Remote: Shimano SL-MT500 I-Spec EV

* In seltenen Fällen liefern unsere Hersteller Fahrräder mit geänderten, aber gleichwertigen Komponenten.

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SKU: 51172977559

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4.3 ★★★★★
Based on 27 reviews
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Adam
Birmingham, US
★★★★★ 4
Too Dry.
Format: Hardcover
This was a required textbook for my class in college. I think it was too dry. The book titled Deep Learning: From Curiosity To Mastery is much more approachable.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on May 22, 2026
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Amazon Customer
Lowell, US
★★★★★ 5
Comprehensive! The Bible of Deep Learning!
This book has by far surpassed my expectations! I have purchased many machine learning and deep neural network books in the past, but nothing has ever come close to this book! First of all, it is written by the fathers of Deep Learning, and is therefore an authority. Secondly, the book is broken into three parts: 1. A math overview and refresher. 2. Deep Learning applications and 3. Research in Deep Learning. I can't help but go through this book from front to back. It is a smooth read, and every sentence written is meaningful. These guys know their stuff! And after you read this book, YOU WILL ALSO know your stuff! If you feel daunted by the price, just remember, you get what you pay for! I'd say they could easily charge about $300+ for this book, but they are doing everyone a very kind favor by ONLY charging this reasonable amount. You get A LOT of bang for your buck with this purchase. I hesitated at first about buying this book because of the price, but I am soooooo happy that I did! Worth every penny! Look no further, get this book and start your Deep Learning journey!!
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Reviewed in the United States on July 14, 2017
M
Verified Purchase
mackster
Grantham, US
★★★★★ 1
A rushed, poorly written guide of how the "experts" can't really explain what Deep Learning is
Format: Hardcover
This book, in every sense of the word, is rushed. I think the authors wanted to establish themselves as leaders of this young-ish field, but does so by sacrificing quality. It also shows that Deep Learning theory has been there for a long time, known by another name called Neural Networks. The interesting algorithms are of MLP, Back Propagation and the classical neural networks. The optimization methods such as Adam are the ones that are new and interesting, and the only ones worthy of in this book. So, essentially, what you get from this book is use A for X, B for Y and C for Z type of dry, un-intuitive, badly written waste of paper. As for the structure of the book, it's like an example of how not to structure a book. It has some linear algebra, probability at the start (not good enough, and confuses more people and wastes paper). Goes on to prove other algorithms such as PCA (yeah, ok!). Then, talks about how this architecture works for this and that architecture. So, yeah, if you really want to try out deep learning, don't buy this book. Set up Tensorflow/pytorch/ other library, run the tutorials, find an architecture for the problem you are interested in and start tweaking that. You will have far more fun and would have saved your money. The praise that this book gets is beyond me. Did Musk even read this book? I doubt it.
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Reviewed in the United States on May 15, 2018
S
Verified Purchase
Stergios Papadimitriou
Natrona Heights, US
★★★★★ 5
The classic textbook on Deep Learning
Format: Hardcover
Deep Learning is the promising direction towards general purpose effective artificial intelligence. There is an explosion of fruitful research in recent years and a lot of applications pursued mainly from technology giants as Google, Amazon, etc. and outstanding research institutions. The book "Deep Learning " by Ian Goodfellow, Yoshua Bengio, Aaron Gourville, is an excellent piece of work. They manage to present rather difficult things in an understandable manner. The theoretical presentation is outstanding typical of "classic" books. Also, the book stays close to the practical applicability of all the methods and discusses applications extensively. There are a lot of other useful books on deep learning that follow a more practical approach by focusing on a particular deep learning software package, but this one book is certainly much more essential since it provides the required theoretical background in order to be able to do serious work on deep learning. I consider the book as "must have" for anyone that works on deep learning either in an academic or in an industrial environment.
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Reviewed in the United States on August 25, 2018
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Verified Purchase
Sabrina
Houston, US
★★★★★ 5
100% Recommend
Format: Paperback
Invincible Compendium One completely lived up to the hype. From the very first chapter, I was hooked by the story, the action, and the character development. What starts off feeling like a classic superhero story quickly becomes something much deeper, darker, and way more emotional than expected. The artwork is incredible and the fight scenes are intense without feeling repetitive. Every character feels important and layered, especially Mark and Omni-Man. The pacing is excellent for such a massive collection, and it’s hard to put down once you start reading. If you’re a fan of superhero comics but want something with real stakes, shocking twists, and strong storytelling, this is absolutely worth reading. Easily one of the best graphic novels I’ve picked up in a long time.
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Reviewed in the United States on May 23, 2026

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