SKU: 40225623887
succulents box subscription

succulents box subscription Monthly Subscription Box

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Ships within 48 hours · Estimated delivery Sep 6 - Sep 11

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For Your Every Summer RSVP, with Code: SUMMER15

Description

succulents box subscription Monthly Subscription BoxSucculents Depot Monthly Subscription Box offers fresh, unique, organically grown succulents delivered to your door every month. FREE Plant in April & November every year We would love to celebrate spring and holiday season with you! We will include 1 additional free plant every April and November. Each plant is carefully curated by hand, ensuring that your collection stays diverse and fresh. The plants selection for the upcoming month will be posted

Succulents Depot Monthly Subscription Box offers fresh, unique, organically grown succulents delivered to your door every month.


FREE Plant in April & November every year

We would love to celebrate spring and holiday season with you! We will include 1 additional free plant every April and November.


Each plant is carefully curated by hand, ensuring that your collection stays diverse and fresh. The plants selection for the upcoming month will be posted on the website on or before the 30th of the current month.


Cancel anytime, skip any months, change shipment dates, no questions asked. If you will be away or if you don't like the succulents selection for the upcoming month, you could easily change the shipment date or skip a month. Simply log on to your account and manage the subscription settings anytime.

BEST VALUE. Highest quality and lowest price guarantee. This is the simply the best succulents subscription product you would ever find, with flexible plans tailored to your budget and needs.

 

March 2026 Plants List

1st Plant: Aeonium arboreum Webb & Berthel

2nd Plant: Haworthia cuspidata 'Star Window Plant'

3nd Plant: Graptosedum 'Francesco Baldi'

4th Plant: Crassula nudicaulis var. herrei

5th Plant: Echeveria elegans

February 2026 Plants List

1st Plant: Aeonium 'Phoenix Flame'

2nd Plant: Senecio radicans Hybrid 'Fish Hooks'

3nd Plant: Crassula swaziensis 'Money Maker'

4th Plant: Sedum dasyphyllum 'Corsican Stonecrop'

5th Plant: Taciveria tasha

See historical plants list


Shipping Rate

Shipping cost is calculated during checkout, based on the shipping weight of the subscription box and the destination address. We offer the best discounted shipping rate. Our price (subscription fee + shipping cost) is easily the best value you could ever find.



Shipping Time & Monthly Charge

Your first subscription box will be shipped within 1-3 business days of purchase. Future monthly subscription orders will be processed every month automatically. Your will automatically be charged the same monthly fee and shipping every month (if applicable, sales tax would be applied and it is subject to change based on government sales tax ordinance).


Heat Pack

If you live in an area with temperature that could fall below 40 degrees Fahrenheit around and during winter, please select the Heat Pack option and it will protect the plants from freezing weather during shipping.

If Heat Pack option is selected:

  • During colder months (November - March), one 72 Hour Heat Pack will be included in the subscription shipment box.
  • During warmer months (April - October), instead of the heat pack, we'll include an extra 2" plant to your subscription box.
  • If you select "1 Plant" + "Heat Pack" option, you'll always receive 1 plant + 1 free plant every month.


Shipping & Handling

You will receive a very similar plant to the one shown in the photos; shape and color may vary.

The 2" plants are shipped with the pot and soil.

Ship within USA & its outlying territories only.

Please visit Order Processing & Shipping info page for additional details.


Care Instructions

Please visit our Succulent Care info page for more details.

To ensure the health of succulents, it is important to plant them in porous, well-draining soil. Succulents require little watering, but don't like to sit in wet soil. To create an adequate cactus mix, simply add pumice, perlite, or grit to cactus soil to provide the proper drainage.

Make sure to leave drought periods between waterings to prevent the plant from water-logging.

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: 40225623887

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Walter Echo-Hawk, author of THE SEA OF GRASS.
Phoenix, 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
Draper, 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
Pawtucket, 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
Belleville, 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
Dallas, 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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