SKU: 23486645592

noeifevo 25 2v 10a lithiumbatterijoplader voor 22 2v 6s batterij automatische uitschakeling aluminium behuizing met ventilator

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Description

noeifevo 25 2v 10a lithiumbatterijoplader voor 22 2v 6s batterij automatische uitschakeling aluminium behuizing met ventilatorVoordat u een oplader koopt, bevestig dan of uw batterijtype, nominale spanning, oplaadspanning en de acceptabele oplaadstroom (aanbevolen 0,2C oplaadstroom) overeenkomen met de onderstaande productomschrijving. Als u niet zeker weet of de oplader geschikt is voor uw batterij, neem dan contact op met onze klantenservice voor hulp. Specificaties Ingangsspanning: 220 V Uitgangsspanning: 25,2 V (de oplaadspanning voor de batterij) Oplaadmethode: CC CV

Voordat u een oplader koopt, bevestig dan of uw batterijtype, nominale spanning, oplaadspanning en de acceptabele oplaadstroom (aanbevolen 0,2C oplaadstroom) overeenkomen met de onderstaande productomschrijving. Als u niet zeker weet of de oplader geschikt is voor uw batterij, neem dan contact op met onze klantenservice voor hulp.

 

Specificaties

  1. Ingangsspanning: 220 V
  2. Uitgangsspanning: 25,2 V (de oplaadspanning voor de batterij)
  3. Oplaadmethode: CC/CV
  4. Oplaadstroom: 10 A
  5. Geschikt voor: 6S 22,2 V lithiumbatterij (niet voor loodaccu’s)
  6. Gewicht: 0,8 kg
  7. Afmetingen: 135 x 90 x 50 mm
  8. Bedrijfstemperatuur: -20 °C tot +45 °C
  9. Efficiëntie: > 85 %
  10. Oplaadstekker: EU-stekker (als u een andere stekker nodig heeft, neem dan contact op met onze klantenservice)
  11. Optionele oplaadstekker types: XT60, XT90, Anderson 50A, Anderson 45A krokodilklem, M8, M25, XLR, IECC13, GX16-2 (1+2-), GX16-3 (1+3-) enz. (Als de versie die u nodig heeft hier niet wordt vermeld, neem dan contact op met onze klantenservice)
  12. Hoogwaardige aluminium behuizing met koelventilatoren zorgt voor een soepele werking van de oplader.
  13. Toepassingen: Batterijen, elektrische gereedschappen, e-bikes, scooters, elektrische voertuigen, auto’s, golfkarren, robots, enz.

 

Beschermingsmodus

  1. Kortsluitbeveiliging
  2. Overstroombeveiliging
  3. Overspanningsbeveiliging
  4. Polariteitsbeveiliging
  5. Oververhittingsbeveiliging

 

Gebruik:

  1. Controleer voor gebruik of de batterijoplader geschikt is voor het type opladermodel. Als het model niet past, kan het laadproces abnormaal zijn en kan de batterij ernstig beschadigd raken.
  2. De batterij moet correct worden aangesloten. Verander de polariteit niet! (Rood + Zwart- of Bruin- Blauw + of Rood + Blauw -).
  3. Steek de stekker in het stopcontact en de oplader begint met het opladen van de batterij.
  4. Wanneer de spanning vol is, trek eerst de oplader en daarna de batterijstekker los.

 

Inhoud verpakking 1 x 25,2 V 10 A oplader

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SKU: 23486645592

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Adam
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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.
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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
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mackster
Fort Morgan, 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
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Stergios Papadimitriou
Charlottesville, 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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Sabrina
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Format: Paperback
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Reviewed in the United States on May 23, 2026

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