SKU: 87005459673
neon pothos lowes

neon pothos lowes Pothos Neon Marble

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Description

neon pothos lowes Pothos Neon MarbleYou have to love the bold, bright color of Neon Pothos, right? Neon Marble is a fun upgrade! This sport features the golden yellow color youre used to, but with subtle white marble variegation. Its an elegant, but delightfully easy to grow climbing trailing houseplant thats also hard to find. Beautiful, its also versatile. You can enjoy it trailing from a hanging basket, growing horizontally on a desk or tabletop, or climbing up a moss pole or other

You have to love the bold, bright color of Neon Pothos, right? Neon Marble is a fun upgrade! This sport features the golden-yellow color you’re used to, but with subtle white marble variegation. It’s an elegant, but delightfully easy to grow climbing/trailing houseplant that’s also hard to find.

Beautiful, it’s also versatile. You can enjoy it trailing from a hanging basket, growing horizontally on a desk or tabletop, or climbing up a moss pole or other structure. (Tip: Grow it up vertically and the leaves will grow larger as it matures.)

You can enjoy it just about anywhere since it doesn’t need any special care. It’s relatively forgiving if you forget to water from time to time (or are travelling away from home for a couple of weeks). It’s not fussy about humidity or other conditions.

Don’t miss out. Order now we’ll hand-select your Neon Marble Pothos fresh from the greenhouses. Our team will carefully pack it up send it out for shipping—no stores or warehouses in between. Shipping and handling are included in the price.

  •      Easy-care: Neon Marble Pothos grows in a wide range of conditions and is beginner friendly
  •        Beautiful: The white-variegated leaves are a gorgeous contrast to other houseplants with dark green foliage
  •         Long-lived: With good care, it can live for decades, making it a great investment
  •      Can climb/trail to 6 feet or more

[bio]

Plant Bio

 

Neon Marble Pothos is easy to grow. It tolerates low light, but grows best (and shows off brightest coloration) in lots and lots of light. Its ideal spot is within about 3 feet of an east-, west-, or south-facing window. Artificial light works, too, if you don’t have a bright window or patio door.

 

Water as the top half or so of the soil dries to the touch. If you’re not sure if your Neon Marble Pothos needs water or not, it’s usually better to wait as it would prefer to be a bit too dry than a bit too wet. It will start to wilt if it gets excessively dry, but it’s best to prevent wilt if you can.

 

This climbing/trailing variegated houseplant grows well in average household temperatures, but thanks to its tropical roots, it holds up to heatwaves and doesn’t require particular care when the mercury soars. Do try to keep it over about 50F/10C for best results.

 

It does all right in average household relative humidity levels but prefers above-average relative humidity (over 50 percent) if you’re able to provide it.

 

Note: This plant may have some natural degree of toxicity and may cause discomfort or illness if ingested. Additionally, exposure to the sap of this plant may cause discomfort to individuals with a sensitivity to it upon contact. Grown for ornamental purposes and not intended for human or animal consumption.

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SKU: 87005459673

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Walter Echo-Hawk, author of THE SEA OF GRASS.
Waukegan, 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
Omaha, 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
Charlottesville, 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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Verified Purchase
Amazon Customer
Dallas, US
★★★★★ 4
Just learning it
Format: Paperback
Nice learning book just have to finish it
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Reviewed in the United States on December 10, 2025
K
Verified Purchase
Kindle Customer
Louisville, US
★★★★★ 5
Very useful book
Format: Paperback
I use it for the machine learning class I teach.
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Reviewed in the United States on May 3, 2026

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