SKU: 26486913621

MaggieFrame Magnetic Hoop 3.9" | 100x100mm for MEXA

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Description

MaggieFrame Magnetic Hoop 3.9" | 100x100mm for MEXAMaggieFrame embroidery magnetic hoops are innovative tools for your MEXA embroidery machines! These embroidery hoops magnetic are designed to make stitching easier, more efficient, and more enjoyable than ever before. Packing List: 1. Hoop Main Part x 1 pcs 2. Metal Brackets x 1 pair 3. Screws & Screwdriver (Note: Brackets will be matched according to your machine brand, and need to be assembled on hoop main part with screws) Watch video Compatible

MaggieFrame embroidery magnetic hoops are innovative tools for your MEXA embroidery machines! These embroidery hoops magnetic are designed to make stitching easier, more efficient, and more enjoyable than ever before.

Packing List:

1. Hoop Main Part x 1 pcs
2. Metal Brackets x 1 pair
3. Screws & Screwdriver
(Note: Brackets will be matched according to your machine brand, and need to be assembled on hoop main part with screws)

Watch video

Compatible with MEXA embroidery machines and other models that support magnetic hoops.

For MEXA-JUMBO/ MEXA – Longer/ MEXA – Vego/ MEXA – DUO-BLACK/ MEXA M415/ MEXA M615/ MEXA M815/ MEXA – Duo C etc. embroidery machine, MaggieFrame has 17 hoop sizes to compatible with different machine models of MEXA Embroidery Machines. Click Here to check all 17 sizes for MEXA.

Powered by strong magnetic force, the MaggieFrame embroidery magnetic hoop makes your hooping process super-easy and stable for perfect embroidery results.

Watch video

Hooping Revolution – Magic of MaggieFrame Magnetic Hoop

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MaggieFrame vs Mighty Hoop: Which One is Easier to Use? Has Stronger Magnets? has Higher Durability?

MaggieFrame magnetic embroidery hoops are compatible with a variety of embroidery machines, like Ricoma, Tajima, Brother, Barudan, BAI, HappyJapan, SWF, ZSK, Melco and other Chinese brands. These versatile hoops come in inner sizes from 4″x4″ (100x100mm) to 17″x15.5″ (430x390mm), suitable for different projects such as sweatshirt, towel, right chest logo, jeans, hat, and jacket embroidery.

Our innovative embroidery hoop magnetic design allows you to hold fabric in place easily. With strong magnets, the MaggieFrame magnetic hoop keeps your fabric taut, ensuring smooth and precise embroidery every time.

Customer Reviews:

Watch video

Say Goodbye to Hoop Marks: Sweater Embroidery with MaggieFrame Magnetic Hoops & HoopTalent Station - Customer Using Reference

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Effortless Large Designs with MaggieFrame – Mastering a 17x16 Magnetic Hoop on a 15-Needle Machine - Customer Using Reference

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We have a lot of different size hoops to compatible with MEXA Embroidery Machines. Click Here to check all products for MEXA embroidery machines.

For more product options, browse our full Embroidery Hoops and Other Products collection .

FAQs

I mainly embroider polo logos. How do I choose between different sizes?

For polo logos, the 5″ (127 mm) embroidery magnetic hoop is typically the best fit, providing the right balance between control and space. The 7″ (178 mm) version allows flexibility for slightly bigger or stacked logo designs on MEXA embroidery machines. Both options keep fabric tight, ensuring clean stitching and high accuracy.

For a new employee, which has a shorter learning curve: training them on this magnetic frame or on a traditional screw hoop?

The MaggieFrame magnetic hoop is far easier to learn. Its snap-and-go structure simplifies the hooping process for MEXA embroidery machine users. New operators can achieve proper tension quickly without adjusting screws. This efficiency shortens training time, reduces waste, and keeps embroidery production steady across multiple fabric types.

What should I do if I notice the fabric slipping slightly during the embroidery process?

If slipping occurs, check three common causes: first, the stabilizer may be too light for your design; second, thick or slick fabric might benefit from grip tape inside the magnetic hoop; and third, a smaller embroidery magnetic hoop often prevents fabric stretch. Proper setup on your MEXA embroidery machine usually eliminates these minor issues.

When using this magnetic frame, should the stabilizer be placed inside the frame or 'floated' outside of it?

For most projects, sandwiching the stabilizer with your fabric inside the MaggieFrame magnetic hoop yields the most stable results. For tough-to-hoop materials or bulky items, floating—placing the stabilizer under the bottom frame—can be effective. Both techniques deliver clean outcomes on MEXA embroidery machines when proper tension is maintained.

Shipping Notes
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Exchange/Return Notes
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SKU: 26486913621

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4.5 ★★★★★
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Verified Purchase
Par
Port Orchard, 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.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on December 20, 2024
R
Verified Purchase
Richard Hackathorn
Pawtucket, 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
Port Orchard, 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
Charlottesville, 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
Lake Worth, 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

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