SKU: 86465929335
dresser for clothes

dresser for clothes Unikito 5 Drawer Dresser with Full Length Mirror and Power Outlets, Suitable for Bedroom, Halllway White

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Description

dresser for clothes Unikito 5 Drawer Dresser with Full Length Mirror and Power Outlets, Suitable for Bedroom, Halllway WhiteDresser with Clothes Rack: This dresser is a 2 in 1 design (dresser + closet) with practical hangers for hanging your daily clothes and keeping your bags on the baseboard. The 5 wide and deep drawers next to the hangers can hold 90 120 pairs of socks, 50 60 coats or 70 80 pairs of jeans. With this one piece dresser closet, you can hang and store your clothes and accessories more conveniently without the need for 2 pieces of furniture. Bedroom Dresser

Dresser with Clothes Rack: This dresser is a 2-in-1 design (dresser + closet) with practical hangers for hanging your daily clothes and keeping your bags on the baseboard. The 5 wide and deep drawers next to the hangers can hold 90-120 pairs of socks, 50-60 coats or 70-80 pairs of jeans. With this one-piece dresser closet, you can hang and store your clothes and accessories more conveniently without the need for 2 pieces of furniture.

Bedroom Dresser with Full-Length Mirror: this bedroom dresser is perfect for dressing up as it features a full-length mirror design. With the mirror right on the side of the dresser, you can check your appearance immediately after getting dressed without having to go anywhere else. Such a convenient design will facilitate your daily use and keep you happy all day long!

Dresser with Charging Station: This wide and tall dresser has 3 AC ports and 2 USB ports built into the tabletop to charge up to 5 devices at once. This convenient charging station is within easy reach and easy to use. It also comes with a TV stand that holds a 45-inch TV.

5 Drawer Dresser with LED Lights: This dresser is equipped with a light strip with more than 6000 colors, which can be DIY any color as you like. Its timing, rhythm and music functions allow you to enjoy and create a home atmosphere.

Installation Diversity and Wide Application: the dresser can be installed in the left or right version according to your needs. It is suitable for bedrooms, living rooms, and entrances.

 

Unikito 5 Drawers 2-1 Dresser + Closet Organizer with Full-Length Mirror & Power Outlets & LED Lights

Do you bother with no place to organize your clothes well? Do you need a place to hang and store your things within reach? Our 2-1 dresser will satisfy your needs.


What are our Advantages?

  • Full-Length Mirror - When you put on the clothes you can check your look immediately without going to another place. (Please tear off the protective film before use)
  • 2-1 New and Practical Design - Dresser and closet with both hanging and storing functions which is useful and cost-effective.
  • 5 Big Drawers - Can store at least 90-120 socks, 50-60 Coats, or 70-80 jeans. It's twice bigger than other small drawers.
  • Power Outlets and LED Lights - Handy changing station convenience your life. Wonderful RGB lights decorate your home.
  • Lockable Wheels and Hooks - The rolling dresser makes it easy for you to move to different rooms. 2 hooks as gifts, handy to hang your bag or hats.
  • Left / Right Version and Spacious Desktop - Can be installed in the left or right version depending on your needs. Wooden desktop is sturdy and durable.
  • Wide Application - Perfect for bedroom, entryway for clothes, toys, and accessories storing. As TV Stand--up to 45 Inch.


Specifications:

Size: 15.7"D x 45.3"W x 45.3"H

Product Weight: 43.9 lb

Package Included: 1 x Dresser, 1 x Full-Length Mirror, 1 x Assembly Kit, 1 x Assembly Manual.

We will attach an extra screw for all types screws, so no need to worry about the situation of missing screws.

Children are forbidden to climb on the dresser.


Q&A

Q: How tall of the mirror?

A: The full-length mirror is almost as tall as the dresser which is about 45 Inches, please check the size before purchase.

Q: Are the wheels lockable?

A: Yes, the wheels of the dresser can be lockable, you can move and stop it as you need.

Q: Is the dresser include power outlets and LED strip, right? How to control the lights?

A: Yes, both outlets and LED strip are included, and you can control LED lights with a remote controller( included) or your phone app.

Q: What can I do if it damages or misses any parts?

A: You can message us via Amazon, we will solve the problem for you in 24 Hours.

Shipping Notes
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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]
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SKU: 86465929335

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Walter Echo-Hawk, author of THE SEA OF GRASS.
Louisville, 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.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on April 1, 2019
P
Verified Purchase
Par
Battle Creek, 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
Grantham, 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
New York, 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
Houston, 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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