SKU: 19477534190
trellis for plants near me

trellis for plants near me Natural Cedar Wall Mounted Trellises

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Description

trellis for plants near me Natural Cedar Wall Mounted TrellisesMade in The USA Available exclusively at Eartheasy Wall mounted wood trellises can be attached to fences or the sides of houses, to grow flowering vines, like honeysuckle, jasmine and wisteria! Made in the USA from durable cedar, these wall mounted trellises are available exclusively at Eartheasy. Read more Built to last season after season, these solid cedar garden trellises are a beautiful addition to your home, garage, fence line, shed. Mounted

Made in The USA - Available exclusively at Eartheasy

Wall mounted wood trellises can be attached to fences or the sides of houses, to grow flowering vines, like honeysuckle, jasmine and wisteria! Made in the USA from durable cedar, these wall mounted trellises are available exclusively at Eartheasy.

Read more

Built to last season after season, these solid cedar garden trellises are a beautiful addition to your home, garage, fence line, shed. Mounted above a pot or planter, they are perfect to support flowers and small vining vegetables, like sweet peas, snap peas, patio variety cucumbers, cherry tomatoes, and more!

The vertical and horizontal cross pieces are 1" thick with rounded edges to support heavier plants without cutting into the stems. The notched dadoed crosspieces fit together to form a tight grid, which we have found to be stronger than traditional lattices. The notch itself is 0.5" deep in the 1" thick piece. The squares of the grid measure between 4.5" and 5". The width of the outer frames is 1-5/8".

Features & Benefits:

  • Sturdy design: Provides robust support for climbing plants to grow vertically
  • Solid cedar construction: Unique tongue and groove assembly is strong and lightweight, superior to other wood trellises
  • Enhances garden design: Create a visually appealing focal point along a fence or on a patio
  • Improved airflow & plant health: Elevating plants off the ground promotes better air circulation, reducing risk of diseases and minimizing contact with pests and soil-borne diseases, for healthier plants and harvests
  • Easy Assembly: Trellises easily mount to a wall or fence, all mounting hardware included
  • Made in the USA

Assembly:

Straightforward assembly with just a power drill. Garden wall trellis kits come with detailed instructions, hardware and wood glue. Assembly involves arranging the vertical and horizontal cross pieces on a flat surface, then gluing the notches and applying pressure to form a grid. Once the cross pieces are in place, the frame can be attached with included screws, again applying wood glue to the notches where the cross pieces join the frame.

Wall mounted trellises can be attached to fences, sheds, or the siding of your house or garage.

These cedar garden trellises can be painted or stained, or left unfinished to weather naturally. We offer Eco Wood Treatment as one option. Eco Wood Treatment works by penetrating wood fibers to create a natural buffer against water and fungal decay. It increases wood's durability while creating an aged, silvery patina after just a few hours.

We recommend letting the boards sit in a garage, shed or covered area for 3-5 days to allow the boards to acclimatize to their new environment. This helps to prevent any cupping, warping, and gapping.

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: 19477534190

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Walter Echo-Hawk, author of THE SEA OF GRASS.
Whiting, 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
P
Verified Purchase
Par
Alexandria, 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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Verified Purchase
Richard Hackathorn
Los Angeles, 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
Dallas, 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
Carnegie, 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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