SKU: 99757473343

Reef Little Salty Slide Black Swell Checker

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Description

Reef Little Salty Slide Black Swell CheckerReef Little Salty Slide Black Swell Checker Reef is opgericht in 1984 door de Argentijnse broers Fernando en Santiago Aguerre, vanuit een liefde voor surfen en een gebrek aan goede strandsandalen. Wat begon als een slipper voor de surfer is uitgegroeid tot een van de meest herkenbare namen in sandalen wereldwijd. De Little Salty Slide is Reef's kindvriendelijke slide voor de allerkleinsten: een watervriendelijke instapper met een verstelbare riem die

Reef Little Salty Slide Black Swell Checker

Reef is opgericht in 1984 door de Argentijnse broers Fernando en Santiago Aguerre, vanuit een liefde voor surfen en een gebrek aan goede strandsandalen. Wat begon als een slipper voor de surfer is uitgegroeid tot een van de meest herkenbare namen in sandalen wereldwijd. De Little Salty Slide is Reef's kindvriendelijke slide voor de allerkleinsten: een watervriendelijke instapper met een verstelbare riem die meegaat op elk avontuur.

Bij Revert 95 in Haarlem hebben we al jaren een van de grootste selecties Reef slippers van Nederland. De Little Salty Slide Black Swell Checker is een stoere, speelse keuze voor de kleintjes.

De slide

De Reef Little Salty Slide is gebouwd voor kinderen die de hele dag in beweging zijn. Verstelbare gewatteerde riem voor een instelbare, comfortabele pasvorm die meegroeit met de dag. Zacht, ondersteunend voetbed voor langdurig draagcomfort. Watervriendelijke materialen die gemaakt zijn voor stranddagen, zwembadplezier en alles daartussenin. Makkelijk aan en uit, perfect voor kinderen die zelf hun schoenen willen doen. Black Swell Checker is een stoer zwart-wit geblokt patroon dat direct opvalt.

Specificaties

Kenmerk Detail
Merk Reef
Model Little Salty Slide
Colorway Black Swell Checker
Riem Verstelbaar en gewatteerd
Voetbed Zacht en ondersteunend
Watervriendelijk Ja
Sluiting Instapper met verstelbare riem
Doelgroep Jongens, peuter en kleuter

Maatadvies

De Little Salty Slide valt normaal op maat. De verstelbare riem zorgt voor een instelbare pasvorm. Beschikbaar in maten 3 tot 12 (US kindermaat).

Past bij

Black Swell Checker is een stoer, grafisch zwart-wit patroon dat goed combineert met een zwembroek, een strandoutfit of eenvoudige zomerkleding. De watervriendelijke slide gaat makkelijk aan en uit, ideaal voor kinderen die snel willen. Goed voor het strand, het zwembad of de speeltuin.

Bekijk ook de andere Reef slippers in ons assortiment bij Revert 95 voor de grootste en meest gevarieerde selectie Reef slippers van Nederland.

Waarom bij Revert 95 kopen?

Revert 95 heeft de grootste en meest gevarieerde selectie Reef slippers van Nederland. Opgericht in 1995 vanuit een liefde voor skateboarden en streetwear, verkopen we merken die we zelf dragen en geloven. Bestel online of kom langs in onze winkel aan de Kleine Houtstraat 30 in Haarlem.

  • Snelle verzending vanuit Nederland
  • Afhalen in onze winkel in Haarlem
  • Persoonlijk advies van mensen die het zelf dragen
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SKU: 99757473343

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4.3 ★★★★★
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O
Om S
Carnegie, US
★★★★★ 4
Title: Really Good Book for Learning LLMs
Format: Paperback, Format: Paperback
I picked up this book after struggling with LLM implementation at work. Ken Huang explains things clearly without too much technical jargon. The book covers everything from data preparation to building AI agents. I especially liked the chapters on RAG and prompting techniques - they helped me improve my current projects. The code examples actually work, which is nice. Some parts are pretty advanced, so you need basic Python knowledge. I had to read a few chapters twice to fully get it. The fairness and bias detection section was eye-opening. Good practical advice throughout. Not just theory - real solutions you can use. Worth the money if you're serious about LLM development. Recommended for anyone building AI systems professionally.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on July 25, 2025
J
Jiewen Wang
Phoenix, US
★★★★★ 5
a comprehensive guide at the intersection of generative AI and cybersecurity
Format: Kindle
This book blends deep theoretical foundations with practical frameworks and forward-looking strategies. From adversarial risk models to actionable guidance using OWASP Top 10 for LLMs and the NIST AI RMF, it offers both technical depth and operational clarity. What makes it stand out is its balance of academic rigor and real-world CISO insights, providing a holistic perspective on securing GenAI systems. While it leans enterprise-focused, the content remains accessible to security engineers, risk managers, and policy leaders alike. Generative AI Security is a timely and essential read for anyone working to deploy GenAI responsibly—building systems with both power and integrity in today’s fast-evolving threat landscape.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on July 2, 2025
N
Nader
Waukegan, 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
Omaha, 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
San Leandro, 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.
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Reviewed in the United States on August 10, 2025

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