SKU: 18161157453
buy curly spider plant

buy curly spider plant 3.5”-pot Bonnie Curly Spider Plant, Chlorophytum comosum, Airplane Pla – Wonderland Flora

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Description

buy curly spider plant 3.5”-pot Bonnie Curly Spider Plant, Chlorophytum comosum, Airplane Pla – Wonderland FloraWhat you will get You will receive a Bonnie spider plant growing in a 3. 5" pot. Description Spider plant (Chlorophytum comosum), also known as airplane plant, is a perennial herbaceous house plant. The plant is extremely easy to grow and are excellent for new gardeners or those lacking a green thumb. Fun Points Bonnie spider plant has a leaf color pattern similar to the Vittatum variety but the leaves curl and bend. 1. Very decorative. While pure

What you will get

You will receive a Bonnie spider plant growing in a 3.5" pot.

--------------------

Description

Spider plant (Chlorophytum comosum), also known as airplane plant, is a perennial herbaceous house plant. The plant is extremely easy to grow and are excellent for new gardeners or those lacking a green thumb.

Fun Points

Bonnie spider plant has a leaf color pattern similar to the Vittatum variety but the leaves curl and bend.

1. Very decorative. While pure green varieties are present, the most common spider plant varieties are in a striped green-and-white variegated form. Their energetic, ever-thriving and vibrant looking adds a lively component to your home and office. The curly variety has a special looking and is compact suitable to smaller space.

2. Special and unique plantlets. Spider plants are very special and interesting because of the way of baby spiders (plantlets or spiderettes) growing on the tips of the branching stolons (creeping horizontal stem or runner) dangling from the mother spider plant. In nature, a spiderette starts to develop adventitious roots when it becomes enough large or touches the soil. Baby spiders can also be rooted very easily after cutting off from the stolons.

3. Proven air cleaners. Spider plants are proven air cleaners. When you send a spider plant to a relative or friend, you not only send him/her such a gorgeous gift but also a health guard.

Growing tips.

1. Soil: Spider plants grow the best in fast-draining and well-aerated potting media. The plants may still grow well even if their tuberous roots fill a large portion of the potting space.

2. Light: Spider plants prefer bright indirect light and may grow well under partial direct sunlight, especially when the weather is cooler.

3. Temperature: Spider plants like cooler temperature with an optimal temperature range of 55 and 80°F. Temperature below 50°F should be avoided.

4. Water: Although spider plants can stand in dry or wet soil for quite a while, it would be ideal to keep the soil evenly moist, not too dry or too wet. Make sure to water the pot thoroughly every time.

5. Feeding: Although not very demanding, spider plants may grow better if fertilized during the growing season. Once in a month with a liquid fertilizer at the recommended strength would be sufficient for your plant health.

Special care: Spider plants prefer a semi-pot bound environment. Repotting becomes necessary if their fleshy roots are filling most of pot space and watering becomes difficult. The plant may be divided when repot if it is very large and divisions at the bottom are evident.

Spider plants are sensitive to the fluoride in tap water. Using tap water may also result in minerals building up. If you see your plant having brown leaf tips, it is likely due to too much fluoride and/or salts building up. This may be taken care of by soaking the pot or water it thoroughly a few times with a large amount of water.

Shipping:

Plants are shipped with pots. We offer different shipping methods at checkout.

MOVING YOUR PACKAGE ALONG:
If you notice your package is stuck somewhere during transit, filing an update request on your tracking page may help move your package along. You may also notice us to add such a request from our side.

AVOID DAMAGE:
We take very effective packaging measures to prevent your plants from damages. When the temperature is below freezing point at any transit points, it is important to add one or more heat packs in your order (depending on your package size) to protect your plant from cold damage:

It is also critical to take your package inside promptly upon delivery when it is hot or cold. Heat may accumulate and damage your plants if the package is left under the sun even if the temperature is relatively mild.

Shipping Notes
  • Free Standard Shipping on $100+ Orders to the USA.
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SKU: 18161157453

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4.5 ★★★★★
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Hashi Hanta
Massapequa, 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
Chelsea, 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
W
Walter Echo-Hawk, author of THE SEA OF GRASS.
Omaha, 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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Verified Purchase
Par
Bozeman, 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
Whiting, 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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