SKU: 61509546631
rectangle pots for indoor plants

rectangle pots for indoor plants Flutini

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Description

rectangle pots for indoor plants FlutiniSet of 2 White Fluted Oval Stone Resin Indoor Plant Pots A modern, elevated way to style your indoor plants. This set of two white fluted indoor plant pots combines a clean oval silhouette with a premium stone resin build, giving your home a refined, minimalist touch. Lightweight yet durable, both pots feature a smooth interior, a beautifully ribbed exterior texture, and a crisp matte finish that complements any dcor style. Designed as a matching pair

Set of 2 White Fluted Oval Stone Resin Indoor Plant Pots

A modern, elevated way to style your indoor plants. This set of two white fluted indoor plant pots combines a clean oval silhouette with a premium stone resin build, giving your home a refined, minimalist touch. Lightweight yet durable, both pots feature a smooth interior, a beautifully ribbed exterior texture, and a crisp matte finish that complements any décor style.

Designed as a matching pair with two practical sizes, they’re ideal for creating layered displays on shelves, windowsills, console tables and workspaces.

Stone resin oval plant pots – sizes and dimensions

  • 1× Large white oval pot – Height 13.5cm, Width 21.5cm, Depth 13.5cm, 5mm wall thickness with a volume of 2.9L
  • 1× Small white oval pot – Height 10.5cm, Width 17.5cm, Depth 10.5cm, 5mm wall thickness with a volume of 1.4L
  • Both indoor plant pots made from premium stone resin with a fluted outer texture

Modern white fluted indoor plant pots – key features

  • Contemporary fluted texture for a clean, architectural look
  • Stone resin plant pots offering strength, stability and a premium feel
  • Matching pair in two versatile sizes for layered plant styling
  • Smooth interior suitable for nursery pots or direct planting
  • Lightweight construction for easy repositioning around the home
  • Space-saving oval shape that fits beautifully on narrow surfaces and shelves

Where to use these white oval indoor plant pots

These white stone resin plant pots are designed for indoor use and suit both small and medium houseplants such as ferns, trailing plants, calatheas, succulents, herbs and decorative foliage.

They work perfectly in living rooms, bedrooms, kitchens, home offices, window ledges, sideboards or as part of styled shelf arrangements. The neutral white finish blends effortlessly with Scandinavian, Japandi, modern and minimalist interiors.

Full description – white fluted oval stone resin plant pots

Bring softness and structure to your plant displays with this elegant set of two white oval indoor plant pots. The fluted exterior adds depth and texture, catching the light beautifully throughout the day, while the smooth stone resin body provides durability without the weight of traditional ceramic pots.

The larger pot at 13.5cm tall is ideal for statement indoor plants, while the smaller 10.5cm pot is perfect for compact greenery or cascading varieties. Together, they create a cohesive, minimalist look that instantly upgrades shelves, console tables and window sills.

Whether you’re refreshing a room, creating a styled shelf moment or gifting a plant lover something special, this paired set of white fluted oval plant pots delivers timeless design and everyday practicality for modern homes.

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SKU: 61509546631

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4.3 ★★★★★
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Hashi Hanta
Alexandria, US
★★★★★ 5
Excelllent book
Format: Hardcover
As one of the group of Native Americans who landed on Alcatraz with Richard Oakes, I enjoyed this book. Richard was a fantastic man. A good man.
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Reviewed in the United States on February 14, 2019
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Carol
Lowell, US
★★★★★ 5
Need to read book
Format: Hardcover
The truth about the Native people. THANK YOU Kent for writing this book. We purchased about 12 total.
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Reviewed in the United States on November 24, 2019
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Walter Echo-Hawk, author of THE SEA OF GRASS.
Belleville, 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.
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Reviewed in the United States on April 1, 2019
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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
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Richard Hackathorn
Waukegan, 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

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