SKU: 93592329693

redken frizz dismiss shampoo liter

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Description

redken frizz dismiss shampoo literRedken Frizz Dismiss Shampoo 1000ml Liter wurde speziell entwickelt, um krauses Haar zu bndigen. Die milde Formel ist sanft zum Haar und effektiv gegen Frizz. Das Haar wird sanft gereinigt, whrend Kruseln reduziert und verhindert wird. Mit diesem Redken Shampoo erhalten Sie die Kontrolle ber Ihr Haar zurck, das wunderbar glatt und frei von Frizz wird! Welche Eigenschaften hat das Frizz Dismiss Shampoo 1000ml Liter? Suchen Sie ein Redken Shampoo zur

Redken Frizz Dismiss Shampoo - 1000ml Liter wurde speziell entwickelt, um krauses Haar zu bändigen. Die milde Formel ist sanft zum Haar und effektiv gegen Frizz. Das Haar wird sanft gereinigt, während Kräuseln reduziert und verhindert wird. Mit diesem Redken Shampoo erhalten Sie die Kontrolle über Ihr Haar zurück, das wunderbar glatt und frei von Frizz wird!

 

Welche Eigenschaften hat das Frizz Dismiss Shampoo - 1000ml Liter?

Suchen Sie ein Redken Shampoo zur Reduzierung von krausem Haar? Das Redken Frizz Dismiss Shampoo - 1000ml ist ein absolutes Muss für krauses Haar!

  • Anti-Frizz Shampoo
  • Reinigt das Haar sanft
  • Hilft, das Haar vor Feuchtigkeit zu schützen
  • Erleichtert die Kämmbarkeit
  • Sicher für chemisch gestyltes Haar
  • Speziell für krauses Haar
  • Glättet und verleiht Glanz
  • In praktischer XL-Größe erhältlich: 1000 ml!

 

Wie wenden Sie das Redken Frizz Dismiss Shampoo - 1000ml Liter an?

Für beste Ergebnisse empfehlen wir Ihnen, das Redken Frizz Dismiss Shampoo - 1000ml mit weiteren Haarpflegeprodukten aus der Frizz Dismiss Linie von Redken zu kombinieren.

Schritt 1: Tragen Sie das Redken Shampoo auf das feuchte Haar auf und massieren Sie es ein. Anschließend gründlich ausspülen.

Schritt 2: Verwenden Sie anschließend den Redken Frizz Dismiss Conditioner zum zusätzlichen Schutz vor Frizz. Verteilen Sie den Conditioner gleichmäßig in den Längen, vermeiden Sie den Ansatz und konzentrieren Sie sich auf die Spitzen. Lassen Sie den Conditioner kurz einwirken und spülen Sie ihn gut aus.

 

Tipp: Wir empfehlen, Ihr Haar einmal wöchentlich mit einer nährenden Haarmaske zu pflegen. Verwenden Sie die Redken Frizz Dismiss Maske und geben Sie Ihrem Haar eine pflegende Kur!

 

Was sind die charakteristischen Inhaltsstoffe des Frizz Dismiss Shampoo - 1000ml Liter?

Das Frizz Dismiss Shampoo - 1000ml enthält zwei Inhaltsstoffe, die krauses Haar der Vergangenheit angehören lassen:

Babassuöl – Ein ökologisch verantwortungsvolles und nachhaltiges Öl, das das Haar mit Feuchtigkeit versorgt und ihm Glanz verleiht. Babassuöl ist eine nachhaltige Alternative zu Palmöl.

Aquatoril – Sorgt für optimale Glätte und schützt das Haar vor Feuchtigkeit.

Brazilian Praxaci Oil – Stärkt die Haarfaser und reduziert das Volumen, das durch Krausigkeit entsteht, für geschmeidiges und glänzendes Haar.

AQUA / WATER / EAU CETeaRYL ALCOHOL BEHENTRIMONIUM CHLORIDE PARAFFINUM LIQUIDUM / MINERAL OIL / HUILE MINERALE ORBIGNYA OLEIFERA SEED OIL PARFUM / FRAGRANCE ISOPROPYL ALCOHOL GLYCERIN PHENOXYETHANOL PEG/PPG/POLYBUTYLENE GLYCOL-8/5/3 GLYCERIN BENZYL SALICYLATE DILAURYL THIODIPROPIONATE BENZYL ALCOHOL CHLORHEXIDINE DIGLUCONATE LINALOOL CITRIC ACID HEXYL CINNAMAL GERANIOL AMYL CINNAMAL COUMARIN CITRONELLOLPROPY

 

Wo kann ich meine Frage zum Redken Frizz Dismiss Shampoo - 1000ml stellen?

Sie sind unsicher, ob die Redken Produkte Ihre Erwartungen erfüllen, schwanken zwischen zwei Produkten oder haben eine andere Frage? Kontaktieren Sie uns gerne jederzeit per E-Mail unter [email protected]. Sie können uns auch während der Geschäftszeiten telefonisch erreichen. Unsere Beauty-Experten stehen Ihnen an Werktagen während der Bürozeiten mit Rat und Tat zur Seite!

Kontakt Lieferant:
RedKen
277, rue Saint Honore
75008 Paris
France
[email protected]

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SKU: 93592329693

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4.6 ★★★★★
Based on 30 reviews
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Product Reviews
N
Nader
Pawtucket, 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
Alexandria, 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
Battle Creek, 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
Pawtucket, 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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