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Description
Ruvati Roma 33" Undermount Stainless Steel Workstation Kitchen Sink, 50/50 Double Bowl, 16 Gauge, RVH8350Ruvati 33 inch Workstation Ledge 50 50 Double Bowl Undermount 16 Gauge Stainless Steel Kitchen Sink RVH8350 Convert your kitchen sink into a fully functional workstation with the Roma collection from Ruvati. Featuring an undermount installation and sharp inside corners, modernity is apparent. The workstation design features a built in ledge that provides a platform for Ruvati's unique accessories. Each sink in the Roma collection features a solid
Ruvati 33-inch Workstation Ledge 50/50 Double Bowl Undermount 16 Gauge Stainless Steel Kitchen Sink - RVH8350
Convert your kitchen sink into a fully functional workstation with the Roma collection from Ruvati. Featuring an undermount installation and sharp inside corners, modernity is apparent. The workstation design features a built-in ledge that provides a platform for Ruvati's unique accessories. Each sink in the Roma collection features a solid hardwood cutting board and decorative drain cover. Some also include a stainless steel colander or Ruvati's patented foldable drying rack. With the Roma collection, you can do all your prep work on top of your sink and keep your countertops free of mess.
Please see our color disclaimer.
Features
- WORKSTATION SINK: Ledges on the front and back provide a track for the included accessories.
- 16 GAUGE STAINLESS STEEL: Premium T-304 Grade (18/10 Chromium/Nickel) will never rust or stain.
- LARGE DOUBLE BOWL SINK: 33-inch wide and 19-inch front-to-back gives you plenty of usable space.
- COMMERCIAL-GRADE BRUSHED FINISH: Easy to clean and long-lasting, hides scratches and matches well with your kitchen appliances.
- SOUNDPROOF COATING: Heavy duty thick rubber padding minimizes noise and reduces condensation.
- SHARP INSIDE CORNERS: Experience a more modern look.
- FOLDABLE DRYING RACK (Patented by Ruvati): Constructed of stainless steel bars and a flexible silicone frame, ideal as a dish-drying rack.
- SUPERIOR WOOD CUTTING BOARD: Constructed of solid sapele wood (African Mahogany) that is resistant to water damage and scratches.
- STAINLESS STEEL COLANDER: Hangs nicely over the sink bowl, making it easy to rinse fruits and vegetables right on the sink.
- PROTECTIVE BOTTOM GRID: Made of stainless steel, protects the bottom of the sink from impact and scratches and allows water to flow freely.
- INCLUDES DECORATIVE DRAIN COVER: Hides the drain while allowing waste and water to flow freely.
- EXTERIOR DIMENSIONS: 33" (wide) x 19" (front-to-back)
- INTERIOR BOWL DIMENSIONS: 15" x 16" (left) x 15" x 16" (right) x 10" (bowl depth)
- MINIMUM BASE CABINET: 36"
- 3.5" DRAIN OPENING: Will fit any standard garbage disposal unit.
- INCLUDED IN BOX: Sink, stainless steel colander, solid wood cutting board, dish drying foldable rack, stainless steel bottom rinse grids (set of 2), basket strainer drain assembly (qty 2), decorative drain cover (qty 2), cut-out template, and mounting brackets.
- Ruvati USA Limited Lifetime Warranty
Details
| Basket Strainer Included?: | Yes |
|---|---|
| Bowl Split: | 50/50 |
| Box Height: | 36" |
| Box Length: | 36" |
| Box Weight: | 36 lb(s) |
| Box Width: | 36" |
| Country of Origin: | Vietnam |
| Collection: | Roma |
| Color: | Stainless Steel |
| Depth: | 10" |
| Drain Placement: | Rear Center |
| Finish: | Stainless Steel |
| Grid Included?: | Yes |
| Gauge: | 16 |
| Inner Depth: | 10" |
| Installation Type: | Undermount |
| Item Length (Front to Back): | 19" |
| Item Weight: | 53 lb(s) |
| Item Width (Side to Side): | 33" |
| Material: | Stainless Steel |
| Minimum Cabinet Size: | 36" |
| Number of Bowls: | 2 |
| SKU: | RVH8350 |
Warranty
Limited Lifetime Warranty
Installation Instructions
Installation Instructions (PDF)
Product Specifications (PDF)
Template (RVH8350 TEMPLATE.dxf)
Related Products
Grid(s):
- Ruvati Bottom Rinse Grid for RVH8350, RVH8351 sink, RVA68350
Cutting Board(s):
- Ruvati 17 x 11 inch Solid Wood Replacement Cutting Board for Ruvati Workstation Sinks, RVA1217
Colander(s):
- Ruvati Workstation Sink Replacement Colander 17 inch Stainless Steel with Wooden Handles, RVA1317
Other(s):
- Ruvati Drain Cover for Kitchen Sink and Garbage Disposal - Brushed Stainless Steel, RVA1035
- Ruvati Stainless Steel and Silicone Foldable Drying Rack for Workstation Sinks Dish Mat Trivet, RVA1395
Video(s)
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4.6 ★★★★★
Based on 25 reviews
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Product Reviews
★★★★★ 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
★★★★★ 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
★★★★★ 5
Cover many areas in detail and recommendations for more to read for what's outside
Format: Paperback
Good book!
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Reviewed in the United States on May 4, 2026
★★★★★ 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.
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Reviewed in the United States on March 1, 2022
★★★★★ 5
Thorough Primer for Machine Learning and PyTorch
Format: Paperback
BLUF: A thorough primer for machine learning enthusiasts with plenty of theory to underscore its many practical examples. A definite must-have for anyone looking to add PyTorch to their machine learning tool belt.
PROS:
- Extremely thorough (if not comprehensive). I really appreciate that this book doesn't just thrust one into building models with PyTorch. It starts at the "beginning" and provides examples, theory, additional resources, and citations along the way.
- Theory. Those whose calculus and linear algebra courses ended many years ago will appreciate (if not remember exactly) the mathematical theory and notation that accompanies almost every paragraph. This book gives one the opportunity to "dig deeper" or stay in the shallows until the notation stops.
- Python. Rather than simply utilizing Scikit-Learn to illustrate concepts and introduce models, this book contains many sections where models (such as a Perceptron) are coded from the ground up so the reader can fully understand the underlying mechanics. Python enthusiasts will nerd out. Parents of small children might want to skip a few pages.
- Graphs, charts, and graphics. There are plenty of places where a drier text might have foregone the use of graphs. This text does not. It does however refrain from overusing them.
- PyTorch. This should be obvious from the title, but this text prioritizes PyTorch instead of TensorFlow. This is especially helpful for those looking for an alternative to Keras and TensorFlow as the PyTorch API is very user-friendly.
CONS:
- Almost too much code. This isn't a true "con" but anyone wanting to emulate or follow along with the examples would do well to get the digital edition so they can copy and paste.
- Length and complexity. Anyone hoping for a "quick read" or a "quick start guide" will be disappointed. This book hovers somewhere between an undergraduate primer and a graduate-level text for length and readability. This is not to say that it's difficult to read, merely that there are other "quick start" / "practical" texts out there that cater more to a lay audience.
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Reviewed in the United States on February 26, 2022