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Description
Jackson TH3P R SL filters voor PowerCap InfinityDe originele Jackson TH3P R SL filters (code CAU660000400) zijn ontworpen als vervangonderdeel voor de PowerCap Infinity Powered Air Purifying Respirator (PAPR). Deze filters bieden de hoogst mogelijke TH3bescherming (Nominal Protection Factor 500 UK APF 40 volgens EN 12941: 1998+A2: 2008). Let op: deze filters zijn bedoeld voor het verwijderen van vaste deeltjes zoals stof, sporen, mist en dampen. Zij filteren geen gassen, dampen of toxische stoffen
De originele Jackson TH3P R SL filters (code CAU660‑000‑400) zijn ontworpen als vervangonderdeel voor de PowerCap® Infinity® Powered Air Purifying Respirator (PAPR). Deze filters bieden de hoogst mogelijke TH3‑bescherming (Nominal Protection Factor 500 / UK APF 40 volgens EN 12941:1998+A2:2008).
Let op: deze filters zijn bedoeld voor het verwijderen van vaste deeltjes zoals stof, sporen, mist en dampen. Zij filteren geen gassen, dampen of toxische stoffen en mogen nooit met perslucht worden schoongemaakt – dit schaadt de bescherming aanzienlijk.
Voordelen
- Levering per paar – voor veilige en complete vervanging
- TH3‑klasse hoogste bescherming volgens EN 12941 (APF 40 / NPF 500)
- Geschikt voor vaste verontreinigers: stof, mist, sporen, rook
- Eenvoudig te vervangen met echte parts-only bayonet montage
- Verplichte vervanging van beide filters tegelijk om optimale afdichting te waarborgen
Specificaties
- Merk: Jackson / JSP
- Type: TH3P R SL
- Code: CAU660‑000‑400
- Beschermingsklasse: TH3 Nominal Protection Factor 500 (UK APF 40)
- Geschikt voor: PowerCap® Infinity® Powered Air Purifying Respirator
- Filtering: vaste deeltjes zoals stof, mist, sporen, rook
- Niet filterend voor: gassen, dampen, toxische stoffen
Bestellen
Zorg voor optimale werking en veiligheid van je PowerCap Infinity PAPR door tijdige vervanging van deze originele TH3P R SL filters. Nieuw,
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4.9 ★★★★★
Based on 11 reviews
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Product Reviews
★★★★★ 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
★★★★★ 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
★★★★★ 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
★★★★★ 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
★★★★★ 5
This is the best purchase I’ve made in 2025!
Format: Paperback, Format: Paperback
I don’t even know where to start ever since I finished (in early August, 2025) the whole series of this comic. I have never been this much speechless in my life. It’s my first comic that I’ve ever read and finished it.
I got into invincible through the TV show and I wanted to give a shot on comics because people said it’s even better than the show, and I was blown away just by the tv show until I started reading this.
It didn’t matter how tired I would be and/or how busy I would be, but I’d still make time to grab and read at least some pages very excited.
There are so many parts in this comics where it reflected on my personal life and somewhat opened my eyes of what I had and need to do in my life. It was really fun, exciting, loving, caring, sad and emotional story. This comic has a definitive beginning and a final, conclusive ending.
I loved it overall despite where there were some boring parts, but it all made sense later in the main story. Very well developed characters, stories and art.
Now whenever I pass by my bookshelf and I see these books puts big fat huge smile on my face. I’m glad I have it in my collection. I got to experience in this comic what I couldn’t in real life.
Every other night in random or toughest moment I would think about what would mark do in this situation.
Thank you for this masterpiece ❤️
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Reviewed in the United States on September 18, 2025