SKU: 23377746195
claw gear hose

claw gear hose Clawgear Raider Mk IV Hose Camo

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Description

claw gear hose Clawgear Raider Mk IV Hose CamoClawgear Raider Mk. IV Pant Die Raider Mk. IV Einsatzhose bietet eine hervorragende Mischung aus Passform, Robustheit, Vielseitigkeit und Leichtigkeit. Eine der vielen Verbesserungen gegenber der Generation 3 der Raider Pant ist die Bundweitenverstellung. Sie ist mit einem elastischen Zug perfekt dem Krper anpassbar, um einen besseren Komfort zu gewhrleisten und Bewegungen zu absorbieren. Das Taschenkonzept wurde von Grund auf berarbeitet so wurden

Clawgear Raider Mk.IV Pant

Die Raider Mk.IV Einsatzhose bietet eine hervorragende Mischung aus Passform, Robustheit, Vielseitigkeit und Leichtigkeit. Eine der vielen Verbesserungen gegenüber der Generation 3 der Raider Pant ist die Bundweitenverstellung. Sie ist mit einem elastischen Zug perfekt dem Körper anpassbar, um einen besseren Komfort zu gewährleisten und Bewegungen zu absorbieren. Das Taschenkonzept wurde von Grund auf überarbeitet - so wurden beispielsweise die Cargotaschen um ein von aussen zugängliches Fach erweitert, in welches ein jederzeit griffbereites 30-Schuss Magazin gesteckt werden kann. Die auffälligsten Änderungen finden sich am Kniebereich: Die Kniehöhe ist nun mittels innenliegendem System höhenverstellbar, die Möglichkeit Knieschoner verschiedener Marken zu verwenden, wurde durch ein modulares Einschubfach realisiert. Wir empfehlen hierbei insbesondere den optional erhältlichen TRUST HP von D3O, welcher über das patentierte Knopflochsystem montiert werden kann und einen herausragenden Schutz durch die Aussenhülle als auch die stossabsorbierende Schaumstoff-Innenseite sicherstellt.

Die Raider Mk.IV Pant ist mit vielen praktischen Extras ausgestattet: Der Bund ist für die Verwendung von Rigger & Safety Belts als auch Hosenträgern optimiert und bietet aufgrund seiner leichten Polsterung einen hohen Tragekomfort. Die Hosentaschen bieten ausreichend Platz und ermöglichen selbst mit Handschuhen einen schnellen Zugriff auf die darin verstauten Ausrüstungsgegenstände. Der Kniebereich ist auf der Innenseite mit einem besonderen Stoff ausgestattet, sodass Feuchtigkeit besonders schnell absorbiert werden kann. Die Hose bietet die notwendige Robustheit und NIR Tauglichkeit um auch unter widrigen Einsatzbedingungen bestehen zu können. So werden ausschliesslich Reissverschlüsse von 'YKK' und Nähgarn von 'Amann' in der Produktion verwendet. Die Hauptnähte sind im Dreinadelstich genäht und deshalb dreifach abgesichert.

  • Hervorragender Tragekomfort und grosse Bewegungsfreiheit
  • Für die Verwendung von Rigger & Safety Belts und Hosenträgern optimierter Bund
  • Verstellbare Kniehöhe
  • Einschubfach für Knieprotektoren verschiedener Marken (Protektoren nicht im Lieferumfang inbegriffen)
  • Im Dreinadelstich genähte Hauptnähte
  • NIR Materialien und robuste Verarbeitung
  • NIR Polycotton Mischgewebe (65% Baumwolle, 35% Polyester), original TL Stoff (TL 8305-0302)
  • Reissverschlüsse von 'YKK'
  • Nähgarn von 'Amann'
  • Auf der Innenseite mit dehnbarem und wasserabweisendem Performance Stoff (87% Polyamid, 13% Elastan) ausgestatteter Kniebereich

Clwagear Hosen zäheln zu den ersten militärischen Kleidungsstücken die wir uns zugelegt haben. Zuerst hatten Paddy und Stefan Hosen der Marke, später kamen Kai, Jannis und Steven auch mit Clawgear aufs Feld.

Lieferumfang:

  • 1x Clawgear Raider Mk.IV Pant
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SKU: 23377746195

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4.8 ★★★★★
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Hashi Hanta
Fort Morgan, US
★★★★★ 5
Excelllent book
Format: Hardcover
As one of the group of Native Americans who landed on Alcatraz with Richard Oakes, I enjoyed this book. Richard was a fantastic man. A good man.
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Reviewed in the United States on February 14, 2019
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Carol
Belleville, US
★★★★★ 5
Need to read book
Format: Hardcover
The truth about the Native people. THANK YOU Kent for writing this book. We purchased about 12 total.
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Reviewed in the United States on November 24, 2019
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Walter Echo-Hawk, author of THE SEA OF GRASS.
Lake Worth, US
★★★★★ 5
Native American history at its best!
Format: Hardcover
Kent Blansett's engrossing story about the life & times of the famed Mohawk activist Richard Oakes is Native American history at its best. I appreciated the well-written context provided about the birth, growth and impact of the Red Power Movement and the pivotal role that social justice activism played in the rise of modern Indian nations in the United States today. This scholarly work helps us understand modern Native America and is a "must-read" for every Native American Studies student and scholar, as well as readers interested in important American social justice movements.
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Reviewed in the United States on April 1, 2019
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Par
Los Angeles, US
★★★★★ 5
Excellent book on ML
Format: Paperback
This is a great book on machine learning. Topics covered are extensive - from beginner level to advanced topics including math behind different algorithms. However, not "all" algorithms are covered. Please go through the table of contents. The first part - 11 chapters - covers machine learning concepts and second part covers advanced topics with Pytorch. There are lots of excellent code and they work!! The quality of the book I received is excellent. I have gone through all 742 pages, and it has held up very well!! I used Jupyter notebook to run all examples. I created a new notebook and copied and pasted the code and ran them. This approach worked very well for me. At the same time, I could experiment with my take on the code snippets and definitely added to my knowledge. Only issue I have is on the second part of the book discussing PyTorch: (1) Some packages are a bit older version: e.g., transformer 4.9.1 whereas current version is 4.48+. It took some tweaking/recoding to get the examples working. (2) There is not much discussion on why certain architecture was chosen - e.g., number of layers, is there a rule of thumb on how to improve performance by changing these parameters? Even with CUDA the code run for a long time. Therefore, experimenting with different values of parameters become too time consuming. (3) On the same note, if I can achieve test accuracy of 90%+ using logistic regression and almost the same (perhaps one or two percent better with PyTorch with IMDB movie review dataset and that two much faster why should I use PyTorch for this dataset? Obviously, PyTorch is for certain types of problems. Discussions can be included by not adding to the exhaustive (and apt) contents. Personally I was disappointed by lack of any example on time series. Must have for ML practitioner as a reference and guide.
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Reviewed in the United States on December 20, 2024
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Richard Hackathorn
Fort Morgan, US
★★★★★ 5
Excellent Textbook for Hands-On Learning of ML
Format: Kindle
This textbook is for the serious life-long learners of machine learning. There are at least two ways to ‘consume’ this book. For the expert in ML, this is a textbook to study as a clear comprehensive ML overview and then to dive into sections of interest or ignorance. The concepts are grounded in code examples and are well cited (with links) to sources. Further, this textbook is appropriate if you are TensorFlow-centric and want to broaden into cutting-edge ML models/tools coded in PyTorch. For a new learner to ML, this is a textbook to DO (not just READ) with hands-on and brain-engaged. If you realize that ML is a key life-long skill for your career, consider this textbook as part of a daily learning habit (10-30 min). From personal experience, my advice to the new learner is as follows… First, clone the GitHub repository, setup your Python environment, and study the textbook, while working through the notebooks. Go on tangents and break the code. Do this methodically as part of your daily learning habit, but do not hesitate to jump ahead several chapters to prepare for tomorrow’s meeting. There is enough excellent material here for a full year of ML adventures. I did a similar strategy with Raschka’s first textbook. About four years ago, I had finished Andrew Ng’s Deep Learning Specialization as a student in his first cohort. I knew the concepts well but could not do the actual application coding. I was surprised how my Python coding improved by following Raschka’s clean and elegant style. And Raschka’s code examples were meaty enough to be springboards into working applications. Several textbook editions later, what is different about this new edition? First, it moves you through scikit-Learn (a firm foundation) to PyTorch, instead of TensorFlow. PyTorch is a better stepping-stone, both conceptually and practically. With PyTorch, you will go further with less energy, while being able to convert your efforts into TensorFlow as needed. In addition, most of the cutting-edge ML/AI/DL research is in PyTorch. It is nice to read a recent arXiv paper, clone their repository, click on the Colab tutorial, and replicate their experiments, along with picking up a ton of new coding tricks & tips. I am excited to work through these PyTorch sections to hone my skills. Second, there is a clear recognition of model tracking and tuning practices. This is often a gap in other ML textbooks and courses. Once you progress beyond the simple demo examples in a lecture, you realize that the real work is experiments, more experiments, and still more experiments, so that you must understand what the model architecture and hyperparameters are doing to your dataset. There is good coverage of scikit-Learn pipeline, grid search, model performance, and the like. Third, ML/AI/DL practice is rapidly evolving. Every week new ML packages/services become available that could save much grief on your current project. What is refreshing about Raschka’s textbook series is that he constantly adding cutting-edge topics because he likes to stay current and to help us stay current. Hence, this edition contains recent ML treats as: transformers, self-supervised learning, autoencoders-to-GAN, graph neural networks, DBSCAN, t-SNE (with brief mention of UMAP), and PyTorch-Lightning.
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Reviewed in the United States on February 26, 2022

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