SKU: 10419155506
air plant globes

air plant globes Hanging Air Plant Globe DIY Kit

$26.14 $29.04
Save 10%
No.2 Bestseller on www.warpunited.com >

Pay in installments of $7.26 with ShopPay, AfterPay and Klarna

Shipping Estimate
USA
  • USA
  • CAN

Ships within 48 hours · Estimated delivery Jul 19 - Jul 24

Promo Codes Available:

For Your Every Summer RSVP, with Code: SUMMER15

Description

air plant globes Hanging Air Plant Globe DIY KitCreate your own modern air plant display with our Hanging Air Plant Globe DIY Kit. Designed for plant lovers and creative minds, this all in one kit includes everything you need to build a minimalist glass terrarium at home. Perfect as a unique gift or a relaxing hands on project, each kit features a versatile glass globe that can be hung or styled on a flat surface. Whats included: Glass air plant globe (hang or sit design) Decorative sand (choice of

Create your own modern air plant display with our Hanging Air Plant Globe DIY Kit. Designed for plant lovers and creative minds, this all-in-one kit includes everything you need to build a minimalist glass terrarium at home. 

Perfect as a unique gift or a relaxing hands-on project, each kit features a versatile glass globe that can be hung or styled on a flat surface. 

What’s included:

Glass air plant globe (hang or sit design)

Decorative sand (choice of colour)

Pebbles

Natural branch accents

Moss

One small air plant

Ribbon or string for hanging 

Step-by-step instructions 

Each kit is thoughtfully curated using natural materials, making every finished piece one-of-a-kind. 

 Delivery Note: Available for pickup on its own, or for delivery as part of a $50+ order within Toronto. 

 

ASSEMBLY AND CARE INSTRUCTIONS

 

Step 1: Pour sand into base of glass globe

 

Step 2: Place moss on top of the sand inside globe

 

Step 3: Add branch/bark pieces to inside of globe

 

Step 4: Add decorative pebbles/stones

 

Step 5: Place air plant inside globe

 

Step 6: Add the ribbon/string so you can hang your creation.  

Gently, slip ribbon through the glass hook on top of the globe. 

Tie each end of ribbon/string into a knot. (DO NOT tie knot to the glass hook. It is breakable).

Make sure the knot is tied tightly so it doesn’t slip apart due to the weight of the globe. 

 

Step 7: You’re ready to hang your globe! 

AIR PLANT CARE: Remove your air plant from the globe 1x each week to mist it. 

Allow air plant to dry upside down on a tea towel or paper towel. 

Place air plant back inside the globe. 

 

(NOTE: Never spray water inside globe. Always remove air plant from the globe to spray/mist). 

 

SHARE YOUR PHOTOS OF YOUR CREATION WITH US ON INSTAGRAM! Tag @fernshoptoronto

 

ENJOY YOUR NEW PLANT FRIEND!! 💚

Shipping Notes
  • Free Standard Shipping on $100+ Orders to the USA.
  • Except Preorder products are shipped in 48 hours.
  • Delivery to the USA:
  1. Standard Shipping : 3-10 business days
  • If time is of the essence, please consider selecting expedited delivery for faster service.
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]
  • Please click here for more details>>> Return & Exchange Policy
SKU: 10419155506

Discover Niche Categories That Outsell air plant globes

Top-Converting Item to Boost Your Average Order

4.3 ★★★★★
Based on 26 reviews
Sort
Highest Rating
Newest First
Oldest First
Product Reviews
H
Verified Purchase
Hashi Hanta
Belleville, 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.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on February 14, 2019
C
Verified Purchase
Carol
Port Orchard, 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.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on November 24, 2019
W
Walter Echo-Hawk, author of THE SEA OF GRASS.
Chelsea, 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.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on April 1, 2019
P
Verified Purchase
Par
Phoenix, 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
Chelsea, 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

recommand products

Villandry Window Box
27.08
PlantBest™ Square Coir Pots
22.92
Abbott Collections 7 in. Giraffe Shaped Planter, Beige
24.41
Campania International Medium Orleans Window Box
25.46
Terra Cotta Planter
27.89