SKU: 20697722264

kerasilk smoothing mask

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Description

kerasilk smoothing maskKeraSilk Smoothing Mask ist die ultimative Lsung fr seidiges, glattes Haar ohne Frizz! Diese intensive Maske sorgt fr geschmeidiges, glattes Haar, das den ganzen Tag frizzfrei und Perfect in Form bleibt. Mit Keratin und flssiger Seide bietet die Maske nicht nur ein glattes Finish, sondern hlt das Haar auch bis in die Spitzen hydratisiert und gut kmmbar. Das KeraSilk Smoothing Mask hat einen angenehmen Duft und ist zudem 100% Vegan & PETA zertifiziert!

KeraSilk Smoothing Mask ist die ultimative Lösung für seidiges, glattes Haar ohne Frizz! Diese intensive Maske sorgt für geschmeidiges, glattes Haar, das den ganzen Tag frizzfrei und Perfect in Form bleibt. Mit Keratin und flüssiger Seide bietet die Maske nicht nur ein glattes Finish, sondern hält das Haar auch bis in die Spitzen hydratisiert und gut kämmbar. Das KeraSilk Smoothing Mask hat einen angenehmen Duft und ist zudem 100% Vegan & PETA-zertifiziert!

 

Was sind die wichtigsten Eigenschaften des KeraSilk Smoothing Mask?

Mit dem KeraSilk Smoothing Mask verwandeln Sie Ihr Haar komplett. Hier haben wir die wichtigsten Eigenschaften der Maske für Sie zusammengefasst: 

  • Nährendes Haarmaske  
  • Intensive Feuchtigkeitsversorgung und glättende Wirkung
  • Reduziert Frizz und sorgt für geschmeidige Haarsträhnen.
  • Angereichert mit Keratin und flüssiger Seide 
  • Langanhaltend glatt und frizzfrei.
  • Ideal für krauses und widerspenstiges Haar 
  • Für jeden Haartyp 
  • 100% Vegan
  • PETA-zertifiziert 
  • Frei von: Siliconen, Sulfaten, Farbstoffen, Mikroplastik, Mineralölen

 

Wie verwende ich das KeraSilk Smoothing Mask?

Nach der Haarwäsche (und Conditioner) eine großzügige Menge des KeraSilk Smoothing Mask auf das handtuchtrockene Haar auftragen. Die Maske gut einmassieren, besonders in den Längen und Spitzen. Für eine intensive Feuchtigkeitsversorgung 5 bis 10 Minuten einwirken lassen und anschließend gründlich ausspülen. Für beste Ergebnisse ein- bis zweimal pro Woche anwenden.

 

Was ist das Ergebnis des KeraSilk Smoothing Mask?

Das KeraSilk Smoothing Mask macht Ihr Haar seidig, glatt und frei von Frizz. Ihr Haar wirkt gesund, fällt geschmeidig und bleibt den ganzen Tag in Form, selbst bei feuchtem Wetter.

 

Aus welchen Zutaten besteht das KeraSilk Smoothing Mask?

Bitte konsultieren Sie vor der Anwendung immer die Zutatenliste auf der Verpackung für die genauesten Informationen. 

Water/Aqua/Eau, CeTearyl Alcohol, Isopropyl Palmitate, Behenamidopropyl Dimethylamine, Behentrimonium Chloride, STeartrimonium Chloride, Dipropylene Glycol, Lactic, Acid, Polyquaternium-37, Isopropyl Alcohol, Dicaprylyl Carbonate, Panthenol, Ethylhexylglycerin, Lauryl GlucoSide, Butyrospermum Parkii (Shea) Oil, Tetrasodium Glutamate Diacetate, Saccharomyces CereviSiae Extract, Tocopherol,Lactobacillus Ferment, Phenoxyethanol, Fragrance/ Parfum, Hexyl Cinnamal.

 

Mehr erfahren über KeraSilk Smoothing Mask?

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PS: Wussten Sie, dass Sie ab einem Bestellwert von 40 euro von kostenlosem Versand profitieren? Viel Spaß beim Einkaufen! ♡

Herstellerkontakt:
Kao GerMany GmbH
Pfungstädter Str. 98-100
D-64308 Darmstadt
Deutschland
[email protected]

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SKU: 20697722264

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4.3 ★★★★★
Based on 8 reviews
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Product Reviews
N
Nader
Whiting, US
★★★★★ 1
Light on substance and heavy on flaws
Format: Paperback
The book has a great list of topics, but fails to provide much substance any of them. Most of the provided code is just comments that avoid the actual crux of the issues being discussed. (e.g. #implement the logic to validate XYZ - while the whole point of this chapter is teach how the heck we validate XYZ!) Some parts are plain wrong, for example the part on Graph based RAG is fundamentally flawed as it assumes the text embedding and the graph embedding are in the same latent space. (This is one of many more examples). Seems like the book was rushed, and the author has limited hands on experience (if any). At least we know based on the amount of flaws that it was not written by an LLM
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on December 31, 2025
N
noam barkay
Belleville, US
★★★★★ 5
Excellent book to truly understand LLM design patterns
Format: Paperback
I just finished reviewing Ken Huang's pocket book on LLM Design Patterns, and WOW what an amazing resource! This book is excellent if you want to truly understand how to create and enhance intelligent AI language models, all that in your pocket! Ken makes the difficult things seem surprisingly easy, and that's the real MAGIC. - How to prepare your data for training by making it extremely clean. Developing the brains: the practical aspects of training, optimizing, and maintaining your models. - Learn amazing prompting techniques (such as Chain-of-Thought and Tree-of-Thoughts) to improve your AI's reasoning and problem-solving abilities. Learn everything there is to know about RAGs so that your LLM can incorporate outside expertise. - It also delves into creating "agentic" AI that is capable of action and planning (not only simple plan and execute but also enhanced techniques like ReWoo!) Really, this feels like a useful toolkit, so Ken thank you for that resource Thanks, Idan Habler
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on June 9, 2025
R
Ryan Meyer
West Palm Beach, US
★★★★★ 3
A Broad Overview, But Light on Modern Fine-Tuning
Format: Paperback
I'm currently really interested in fine-tuning LLMs and recently completed my first LoRA-based fine-tuning on a quantized model. I came to this book looking for more detail on fine-tuning. While it touches on the topic, I found the content didn’t quite align with the current state of the field in 2025. Techniques like LoRA, QLoRA, and PEFT weren’t really covered, and the material leaned more toward what I think are older or lower level approaches. That made it harder to connect with what I’m actually working on. That said, when I shifted to other chapters — like the sections on prompt engineering techniques such as Chain of Thought (CoT) and Tree of Thought (ToT) — I found more value. These sections were clearer, and I picked up a few practical insights, like using few-shot examples that walk through the CoT reasoning process. That’s not something I’ve tried before, and I can see how it might help smaller models that struggle with any type of reasoning tasks. Overall, the book feels more like a broad overview of all LLM concepts. For someone exploring many topics across the LLM ecosystem, it offers a wide-ranging introduction. But for readers like me who are actively trying to learn and apply techniques like fine-tuning and quantization, it may leave you wanting up-to-date guidance.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on August 10, 2025
V
Vineeth Sai
Dallas, US
★★★★★ 5
Great foundation read for security!
Format: Paperback
This book is a great read! It builds a strong foundation and I would highly recommend it for builders who are interetsed in building on LLMs and ensuring everything is secure. Security is super important and this book does it justice!
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on June 27, 2025
C
Verified Purchase
CL
Waukegan, US
★★★★★ 5
Loved it
Format: Paperback
I’ve easily read dozens of tech books. I liked this one a lot. Sure, there were boring parts, but most of it was engaging, especially on dry subjects. I previously read “How AI Works” and found this more informative and way more enjoyable. I got through the 700 pages in about 5 weeks while also learning about probability and linear algebra from other books and online sources. I’d love to read something more advanced by the author, maybe getting into more modern applications. I feel more comfortable with the subject and feel I am now ready to conquer more advanced texts. I initially picked this up to give me some background before reading “How to Build a LLM (from scratch)”. I’ve ordered an intermediary Deep Learning with Python book as well, but wouldn’t mind a more advanced theory book to accompany these books. I’ll definitely be rereading sections of this book to further familiarize myself with topics like backpropagation. Highly recommend if you’re looking for a gentle, but broad introduction to the topic.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on November 14, 2025

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