SKU: 16563168528

Wavy Bundle

$22.68 $25.20
Save 10%
No.2 Bestseller on lamcf.fr >

Pay in installments of $6.30 with ShopPay, AfterPay and Klarna

Shipping Estimate
USA
  • USA
  • CAN

Ships within 48 hours · Estimated delivery Sep 20 - Sep 25

Promo Codes Available:

For Your Every Summer RSVP, with Code: SUMMER15

Description

Wavy BundleIncludes Wash In Waves Wave Saving Shampoo, Brush In Waves Daily Training Lotion, and an Ultra Silky Premium Durag. These high quality, safe, effective WAVEBUILDER products are made by us with only the best available ingredients. Wash In Waves Wave Saving Shampoo 6. 9 oz. (204ml)Smart wavers never use any old shampoo or whatever they find in the shower! The wrong shampoo can reverse days of wave work, make waving harder, and make your waves look dull

 

Includes Wash In Waves - Wave Saving Shampoo, Brush In Waves - Daily Training Lotion, and an Ultra Silky Premium Durag.

These high quality, safe, effective WAVEBUILDER products are made by us with only the best available ingredients.

Wash In Waves - Wave Saving Shampoo 6.9 oz. (204ml)
Smart wavers never use any old shampoo or whatever they find in the shower! The wrong shampoo can reverse days of wave work, make waving harder, and make your waves look dull and dry. Many shampoos strip hair of essential moisture and oils with harsh surfactants. Wavebuilder Wash in Waves Wave Saving Shampoo is WAVE SAFE (TM), hair healthy and never strips - but it still cleans hair and scalp fully and leaves hair soft and refreshed. Enriched with keratin and collagen amino acids.

Brush In Waves - Daily Training Lotion 6.3 oz. (185ml)
Brush in Waves is a hair healthy water based “activator” that helps gently make hair more “waveable.” Sealed in moisture makes hair easier to wave and this product is essential to top wavers all over the world. It can be used as often as desired without buildup and is an excellent brushing aid. Never greasy and leaves a nice lasting shine.

SUPERSILKY Premium Durag Design: WB Grid Blue
PREMIUM SUPERSILKY Durag made with exclusive run-resistant fabric. High count overlock stitched edge will not fray. Extremely fine fibers are knit on each side of the material -- for the silkiest and softest fabric possible. Breathable and comfortable to wear all day and all night.  Generous size and perfect fit, with flat top seams that won’t leave lines in your hair. Fully saturated color on both patterns and solids means the color shows through—so when you tie up – the insides of the tails look just as good no matter how you tie it. The color won’t bleed either—to wash, gently hand wash in cold water and air dry.

Shipping Notes
  • Free Standard Shipping on $100+ Orders to the USA.
  • Except Preorder products are shipped in 48 hours.
  • Delivery to the USA:
  1. Standard Shipping : 3-10 business days
  • If time is of the essence, please consider selecting expedited delivery for faster service.
Exchange/Return Notes
  • We offer a 30-day return/exchange service after receiving.
  • Final sale items are not eligible for returns or exchanges.
  • To process your return/exchange, please contact us at [email protected]
  • Please click here for more details>>> Return & Exchange Policy
SKU: 16563168528

Discover Niche Categories That Outsell

Top-Converting Item to Boost Your Average Order

4.2 ★★★★★
Based on 24 reviews
Sort
Highest Rating
Newest First
Oldest First
Product Reviews
R
Verified Purchase
Richard Hackathorn
Houston, 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.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on February 26, 2022
A
Verified Purchase
Amazon Customer
Boise, 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
Grantham, 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
T
Verified Purchase
Tommy Jonsson
Phoenix, US
★★★★★ 5
Cover many areas in detail and recommendations for more to read for what's outside
Format: Paperback
Good book!
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on May 4, 2026
M
Verified Purchase
Moses Kayanda
Lexington, 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.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on March 1, 2022

recommand products

Dr. Joel Kaplan Silicone Support Rings Cock Ring
15.99
Eden Ripple Silicone Textured G-Spot Vibrator Waterproof
41.99
Eclipse Thrusting Rotator Probe Silicone Rechargeable Vibrating Butt Plug with Remote Control
77.99
Sea-Dog 12 AWG Black Primary Wire - 1000' [8012019]
152.00
Sea-Dog 14 AWG Pink Primary Wire - 100' [8014092]
25.99