SKU: 58888517639

Care Long & Strong Serum 3 stuks

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Description

Care Long & Strong Serum 3 stuksKeune Care Long & Strong Serum 3 stuks De Keune Care Long & Strong lijn is een geheel nieuwe lijn binnen het Keune Assortiment. Een wetenschappelijke doorbraak: Dikker en voller haar Klinisch bewezen binnen 60 dagen. Een prachtige ontwikkeling. De Keune Care Long & Strong is ontwikkeld om de hoofdhuid te voeden, het haar te versterken en de natuurlijke haargroei te stimuleren. De Long & Strong Lijn bevat Marine Density Infusion, biomimetische peptiden

Keune Care Long & Strong Serum - 3 stuks

De Keune Care Long & Strong lijn is een geheel nieuwe lijn binnen het Keune Assortiment. Een wetenschappelijke doorbraak: Dikker en voller haar - Klinisch bewezen binnen 60 dagen. Een prachtige ontwikkeling.

De Keune Care Long & Strong is ontwikkeld om de hoofdhuid te voeden, het haar te versterken en de natuurlijke haargroei te stimuleren. De Long & Strong Lijn bevat Marine Density Infusion, biomimetische peptiden en Centella Asiatica. De Long & Strong lijn verminderd haarbreuk en verhoogd de haardichtheid zodat jouw haar er zichtbaar voller en gezonder uitziet.

Marine Density Infusion
De Marine Density Infusion is ontwikkeld om het haar te versterken en de haardichtheid een boost te geven. Het versterkt elke haar van binnenuit. Het haar wordt daardoor dikker en beter bestand tegen schade van buitenaf. Ook verlengt de levensduur van het haar, wordt het haar vollen en verbeterd de algehele gezondheid. 

Biomimetische Peptiden
Biomimetische Lipiden zorgen voor een versterking van de natuurlijke beschermlaag van het haar. Ze vullen tekorten aan in de natuurlijke lipidenlaag (beschermlaag) van het haar. Hierdoor worden de haarschubben versterkt, herstelt de vochtbalans en wordt het haar mooi glad, soepel en pluisvrij.

Centella Asiatica
Centella Asiatica staat bekend om zijn kalmerende en regenererende eigenschappen. Het stimuleert de bloedsomloop en draagt bij aan het transport van gezonde voedingsstoffen naar de hoofdhuid toe. Centella Asiatica versterkt elke haarvezel van de aanzet tot in de punten, bevordert de elasticiteit en herstelt de vitaliteit. Resultaat: Dikker en gezonder ogend haar. 

Het Keune Care Long & Strong Serum helpt de hoofdhuid te herstellen, de haargroeicyclus te verlengen en haaruitval op termijn te verminderen. Het Care Long & Strong Serum is licht en bevat biomimetische peptiden die de natuurlijke groeisignalen van het lichaam nabootsen. Resultaat: gezonder en voller haar vanaf de aanzet. 

Waarom kiezen voor Keune Care Long & Strong Serum?

  • Stimuleert de haargroei: Stimuleert de haargroei vanaf de aanzet. Zorgt voor meer volume en voller ogend haar. 
  • Versterkt en verstevigd: Vermindert haarbreuk en versterkt haarvezels. Helpt zo om haaruitval te verminderen en de veerkracht van het haar te verbeteren.
  • Niet vet: Wordt snel in de hoofdhuid opgenomen. Ideaal voor dagelijks gebruik. Laat geen product resten achter. 
  • Biomimetische peptiden: Ondersteunen en stimuleren de haargroei.

Hoe gebruik je de Keune Care Long & Strong Serum? 

  1. Was het haar met de Keune Care Long & Strong Shampoo en Conditioner. 
  2. Aanbrengen op de handdoekdroge hoofdhuid. 
  3. Breng secuur aan en masseer het serum zacht in. 
  4. Laat het serum intrekken
  5. Niet uitspoelen. 
  6. Style het haar naar wens.

Tip: Gebruik voor het beste resultaat het Long & Strong Serum elke dag, gedurende 60 dagen om de haargroei effectief te stimuleren. 

Resultaat:

  • 94% van de deelnemers aan het onderzoek liet een afname van haaruitval zien. 
  • Bij 94% van de deelnemers aan het onderzoek was er na 60 dagen een toename in de dichtheid van het haar te zien! 

Geur: 

Soleil
Oriëntaals bloemig, Aromatisch en Amber

  • Top: Mandarijn, Bergamot en Lavendel
  • Hart: Oranjebloesem, Jasmijn en Praline 
  • Basis: Vanille, Mos en Droge Amber 
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SKU: 58888517639

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Walter Echo-Hawk, author of THE SEA OF GRASS.
Port Orchard, 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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Verified Purchase
Par
Carnegie, 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
R
Verified Purchase
Richard Hackathorn
Draper, 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
A
Verified Purchase
Amazon Customer
Louisville, 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
Belleville, US
★★★★★ 5
Very useful book
Format: Paperback
I use it for the machine learning class I teach.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on May 3, 2026

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