SKU: 40112708423

UMC9318 Modern Farmhouse Indoor/Outdoor Ceiling Fan, 10" H x 60" W x 60" D, Matte Black Finish, Aerwyn Collection

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Description

UMC9318 Modern Farmhouse Indoor/Outdoor Ceiling Fan, 10" H x 60" W x 60" D, Matte Black Finish, Aerwyn CollectionPRODUCT OVERVIEW: What makes this product different? The UMC9318 brings a refined balance of form and function with its sculptural five blade silhouette and flush mount profile, a design often missing in traditional ceiling fans. Unlike bulkier models, its close to ceiling canopy and aerodynamic blade tapering create both a sleek architectural presence and improved airflow. Finished in a timeless matte black, it offers a modern farmhouse aesthetic

PRODUCT OVERVIEW:

What makes this product different?
The UMC9318 brings a refined balance of form and function with its sculptural five-blade silhouette and flush-mount profile, a design often missing in traditional ceiling fans. Unlike bulkier models, its close-to-ceiling canopy and aerodynamic blade tapering create both a sleek architectural presence and improved airflow. Finished in a timeless matte black, it offers a modern farmhouse aesthetic that feels elevated compared to standard finishes, combining quiet operation with a cohesive, design-forward look perfect for transitional interiors.

Why is this product worth the price?
The Aerwyn ceiling fan (UMC9318) offers exceptional value due to its versatile modern farmhouse design, suitable for both indoor and outdoor use. Its matte black finish adds a touch of modern refinement, and the quiet operation, highlighted in reviews, ensures a peaceful environment. This 60" fan, with its included installation hardware and remote/wall control options, represents a worthwhile investment in comfort and style. Though it lacks integrated lighting, its focus on core functionality and sleek design makes it an ideal choice for those seeking understated elegance and reliable performance.

What value does this product offer over similar options?
The UMC9318 transforms summer evenings into cherished memories, its whisper-quiet motor and sculptural blades creating gentle breezes that rival ceiling fans can't match without rattling or wobbling. While mass-market alternatives use thin stamped metal that warps over time, this Aerwyn's substantial matte black construction and refined engineering deliver years of silent performance. The dual control options and Urban Ambiance's UA Guarantee elevate ownership beyond typical big-box frustrations.

FIXTURE INFORMATION:
  • PRODUCT COLLECTION: Aerwyn
  • TYPE: Indoor/Outdoor Ceiling Fan
  • STYLE: Modern Farmhouse (Learn More), Farmhouse (Learn More), Transitional (Learn More), Natural (Learn More)
  • METAL FINISH: Matte Black (Learn More)
  • BLADE FINISH: Matte Black
  • OPERATION: Remote Control, Wall Control
  • INCLUDES LIGHT: No
  • INSTALLATION HARDWARE INCLUDED: Yes
  • WARRANTY: 1 Year Manufacturer
  • SKU: UMC9318
DIMENSIONAL INFORMATION:
  • DIAMETER: 60"
  • HANGING HEIGHT: 10” (Learn More)
  • CEILING CANOPY/BACK PLATE: 7” x 10”
  • POWER WIRE LENGTH: 84" (Learn More)
  • SLOPED CEILING COMPATIBLE: No (Learn More)
FAN TECHNICAL INFORMATION:
  • NUMBER OF BLADES: 5
  • FAN MOTOR SPEEDS: 6-Speed, Remote Control, Wall Control, Reversible
  • FAN WATTAGE: 31.57 Watts
  • AIR VOLUME CUBIC FEET PER MINUTE (CFM): 5897 CFM
  • CFM PER WATT: 208
  • FIXTURE WEIGHT: 12 lbs
  • ETL/UL RATING: Damp Locations
  • LOCATION RATING: Indoor/Outdoor
  • FIXTURE MATERIAL: Cast Aluminum, Heavy Stamped Steel, Wood
  • BLADES MATERIAL: Solid Wood
  • BLADE PITCH: 15 Degrees
COLLECTION DESCRIPTION:

The Aerwyn Collection features a mid-century modern aesthetic with clean lines and a warm wood tone, designed to bring subtle sophistication to interiors. With its flush-mount profile and sculptural blade layout, the fan is well suited for low ceilings in living rooms, bedrooms, and lounges. Its quiet operation and cohesive design make it both a visual and functional upgrade to a variety of contemporary and transitional settings.This ceiling fan includes a cylindrical motor housing, paired with five slightly curved blades that extend outward in a symmetrical arrangement. The blades have a tapered form with a smooth surface that enhances airflow while maintaining visual balance. The flush-mount canopy sits close to the ceiling, minimizing bulk. At the center of the housing, a circular element—possibly an integrated light or design accent—adds a touch of contrast and detail.Available in Brushed Bronze, Matte Black, Brushed Nickel, Brushed Pewter, Barn Wood Tone, Polished Chrome, Textured Bronze, Gloss White, Walnut Tone, Brushed Brass, and Light Maple Tone as a ceiling fan with a five-blade configuration and flush mount installation.

PRODUCT PDF MANUALS:

view specification sheet
view installation guide

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SKU: 40112708423

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4.2 ★★★★★
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Verified Purchase
Par
Houston, 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
Battle Creek, 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
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
West Palm Beach, 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
Los Angeles, 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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