SKU: 32563708183

48-34 SPACE MARINES: TERMINATOR ASSAULT SQUAD

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Description

48-34 SPACE MARINES: TERMINATOR ASSAULT SQUADTerminator Assault Squads are armed with devastating close combat weaponry perfect for ferocious assaults and savage boarding actions. They rush to engage the enemy's greatest warriors, shredding the foe with lightning claws or shattering their skulls with thunder hammers. This multipart plastic kit builds five Assault Terminators, and their Teleport Homer, for your Space Marines armies in games of Warhammer 40,000. Clad in the finest armour, they are

 

Terminator Assault Squads are armed with devastating close-combat weaponry perfect for ferocious assaults and savage boarding actions. They rush to engage the enemy's greatest warriors, shredding the foe with lightning claws or shattering their skulls with thunder hammers.

This multipart plastic kit builds five Assault Terminators, and their Teleport Homer, for your Space Marines armies in games of Warhammer 40,000. Clad in the finest armour, they are all but impervious to small arms fire, and they dish out grievous amounts of damage in return. The unit can be armed with thunder hammers and storm shields – ideal for taking down the largest and toughest targets – or twin lightning claws to tear hordes of enemy troops to shreds.

The kit includes the following interchangeable parts:
– 5x Left-handed lightning claws
– 5x Right-handed lightning claws
– 5x Left-handed storm shields
– 5x Right-handed thunder hammers
– 5x Helmeted heads
– 6x Bare heads
– 5x Tilting shields
– 15x Purity seals and honour markings

There are also parts to build one of the squad as an optional Assault Terminator Sergeant with a choice of two heads – bare and helmeted – two different tilting plates, along with armour plating and weapons that display more honour markings.

This kit is supplied with 1x Space Marine Infantry Transfer Sheet, containing 758x high-quality waterslide transfers. These include Chapter icons for the Ultramarines, Imperial Fists, Salamanders, and Raptors, along with battlefield role indicators, numbers, numerals, and more.

This kit comprises 144 plastic components, 5x Citadel 40mm Round Bases, and 1x Citadel 25mm Round Base. These miniatures require assembly and are supplied unpainted – we recommend using Citadel Plastic Glue and Citadel Colour paints.

Rules for using these miniatures in your games of Warhammer 40,000 can be downloaded for free from the Warhammer Community website.

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SKU: 32563708183

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A
Verified Purchase
Amazon Customer
Birmingham, US
★★★★★ 4
Just learning it
Format: Paperback
Nice learning book just have to finish it
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on December 10, 2025
K
Verified Purchase
Kindle Customer
Omaha, US
★★★★★ 5
Very useful book
Format: Paperback
I use it for the machine learning class I teach.
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Reviewed in the United States on May 3, 2026
T
Verified Purchase
Tommy Jonsson
Cuba, US
★★★★★ 5
Cover many areas in detail and recommendations for more to read for what's outside
Format: Paperback
Good book!
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Reviewed in the United States on May 4, 2026
M
Verified Purchase
Moses Kayanda
Whiting, US
★★★★★ 5
One of the best machine learning books...
Format: Paperback, Format: Paperback
Machine Learning can often be intimidating whether you are starting out or already a practitioner. It is easy to get stuck on one concept, walk away frustrated, or just copy that code you find on StackOverflow without really understanding what it does. What the authors of this book, Machine Learning with PyTorch and Scikit-Learn, have managed to do is to keep the reader engaged giving a deeper illustration as to how the concepts work. In this book, you get practical code examples, a detailed explanation of how the various library tools work, and exposure to the mathematical concepts behind machine learning algorithms. In addition, what I like about the book unlike many machine learning books is that the authors have managed to intuitively explain how each algorithm works, how to use them, and the mistake you need to avoid. I have not read a Machine Learning book that better explains Transformers as this one does. The authors have managed to give a detailed dive into this model architecture through well-explained codes and illustrations. As a reader, you walk away having intuitively grasped the concepts of attention and self-attention in ways that will make this crucial NLP architecture clear. You get exposed to pre-trained models from HuggingFace library which really helps to have that hands-on experience working with large datasets. As they have done throughout the book, the authors have broken down those complex mathematical operations into simple explanations that are easy to follow. What I generally like about the book is how it seamlessly connects all the chapters, not throwing off the reader. There are numerous external resources quoted throughout the book. This helps spark that curiosity to dig deeper. In addition, you get introduced to PyTorch, getting exposed to all those sophisticated libraries that help the reader learn how to maximize their compute power. I would say it is not intimidating at all even if you have not used PyTorch before. I would recommend this book to anybody seeking a textbook that is both easy to read and modern in its content. If were to rate the book I will give it a 10/10 as it really applies to both beginners and experienced practitioners, covers all the concepts one needs to apply in their operations, and acts as a quick reference.
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Reviewed in the United States on March 1, 2022
G
Verified Purchase
Gabe Rigall
Battle Creek, US
★★★★★ 5
Thorough Primer for Machine Learning and PyTorch
Format: Paperback
BLUF: A thorough primer for machine learning enthusiasts with plenty of theory to underscore its many practical examples. A definite must-have for anyone looking to add PyTorch to their machine learning tool belt. PROS: - Extremely thorough (if not comprehensive). I really appreciate that this book doesn't just thrust one into building models with PyTorch. It starts at the "beginning" and provides examples, theory, additional resources, and citations along the way. - Theory. Those whose calculus and linear algebra courses ended many years ago will appreciate (if not remember exactly) the mathematical theory and notation that accompanies almost every paragraph. This book gives one the opportunity to "dig deeper" or stay in the shallows until the notation stops. - Python. Rather than simply utilizing Scikit-Learn to illustrate concepts and introduce models, this book contains many sections where models (such as a Perceptron) are coded from the ground up so the reader can fully understand the underlying mechanics. Python enthusiasts will nerd out. Parents of small children might want to skip a few pages. - Graphs, charts, and graphics. There are plenty of places where a drier text might have foregone the use of graphs. This text does not. It does however refrain from overusing them. - PyTorch. This should be obvious from the title, but this text prioritizes PyTorch instead of TensorFlow. This is especially helpful for those looking for an alternative to Keras and TensorFlow as the PyTorch API is very user-friendly. CONS: - Almost too much code. This isn't a true "con" but anyone wanting to emulate or follow along with the examples would do well to get the digital edition so they can copy and paste. - Length and complexity. Anyone hoping for a "quick read" or a "quick start guide" will be disappointed. This book hovers somewhere between an undergraduate primer and a graduate-level text for length and readability. This is not to say that it's difficult to read, merely that there are other "quick start" / "practical" texts out there that cater more to a lay audience.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on February 26, 2022

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