SKU: 76184096074
best indoor plants for hanging pots

best indoor plants for hanging pots Epipremnum 'Pearls and Jade Pothos' 6”

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Description

best indoor plants for hanging pots Epipremnum 'Pearls and Jade Pothos' 6”A Compact, Variegated Pothos Made for Cascading Displays Epipremnum aureum Pearls and Jade is a beautifully variegated pothos cultivar known for its creamy white marbling and soft gray green tones. In a hanging basket form, its delicate trailing vines create an elegant cascading effect, making it perfect for shelves, hooks, and elevated planters. Compared to other pothos varieties, Pearls and Jade has slightly smaller leaves and a more refined,

A Compact, Variegated Pothos Made for Cascading Displays

Epipremnum aureum ‘Pearls and Jade’ is a beautifully variegated pothos cultivar known for its creamy white marbling and soft gray-green tones. In a hanging basket form, its delicate trailing vines create an elegant cascading effect, making it perfect for shelves, hooks, and elevated planters.

Compared to other pothos varieties, Pearls and Jade has slightly smaller leaves and a more refined, compact growth habit—ideal for tighter spaces or minimalist interiors.

What Makes Pearls and Jade Special?

  • Soft Variegation: White-edged leaves streaked with cream, jade green, and silvery gray.
  • Compact Growth: Smaller foliage and tighter internodes than standard Golden Pothos.
  • Beautifully Trailing: Perfect for hanging baskets and elevated displays.
  • Beginner-Friendly: Extremely forgiving and adaptable.

Plant Profile

  • Botanical Name: Epipremnum aureum ‘Pearls and Jade’
  • Common Name: Pearls and Jade Pothos
  • Family: Araceae
  • Native Range: Southeast Asia (species origin)
  • Growth Habit: Trailing vine

Ed’s Care Guide

Care Level: Easy

Light: Prefers medium to bright indirect light. Can tolerate lower light, but variegation may fade in very dim conditions.

Water: Allow the top inch of soil to dry before watering. Tolerates occasional drought better than overwatering.

Humidity: Adapts to typical indoor humidity levels.

Temperature: 65–75°F

Feeding: Fertilize monthly during spring and summer with a diluted liquid houseplant fertilizer.

Pruning: Trim vines as needed to maintain fullness and encourage branching.

Propagation: Easily propagated through stem cuttings with nodes.

Common Pests: Spider mites, mealybugs, and scale.

Toxicity: Toxic to humans and pets if ingested.

A Refined Twist on a Classic Pothos

Introduced in the early 2000s, Pearls and Jade quickly became a favorite for its sophisticated variegation and manageable growth. In hanging basket form, it brings effortless movement and texture to any indoor plant collection.

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SKU: 76184096074

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Amazon Customer
Carnegie, 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
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Kindle Customer
Charlottesville, 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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Tommy Jonsson
Phoenix, US
★★★★★ 5
Cover many areas in detail and recommendations for more to read for what's outside
Format: Paperback
Good book!
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Reviewed in the United States on May 4, 2026
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Verified Purchase
Moses Kayanda
Battle Creek, US
★★★★★ 5
One of the best machine learning books...
Format: Paperback, Format: Paperback
Machine Learning can often be intimidating whether you are starting out or already a practitioner. It is easy to get stuck on one concept, walk away frustrated, or just copy that code you find on StackOverflow without really understanding what it does. What the authors of this book, Machine Learning with PyTorch and Scikit-Learn, have managed to do is to keep the reader engaged giving a deeper illustration as to how the concepts work. In this book, you get practical code examples, a detailed explanation of how the various library tools work, and exposure to the mathematical concepts behind machine learning algorithms. In addition, what I like about the book unlike many machine learning books is that the authors have managed to intuitively explain how each algorithm works, how to use them, and the mistake you need to avoid. I have not read a Machine Learning book that better explains Transformers as this one does. The authors have managed to give a detailed dive into this model architecture through well-explained codes and illustrations. As a reader, you walk away having intuitively grasped the concepts of attention and self-attention in ways that will make this crucial NLP architecture clear. You get exposed to pre-trained models from HuggingFace library which really helps to have that hands-on experience working with large datasets. As they have done throughout the book, the authors have broken down those complex mathematical operations into simple explanations that are easy to follow. What I generally like about the book is how it seamlessly connects all the chapters, not throwing off the reader. There are numerous external resources quoted throughout the book. This helps spark that curiosity to dig deeper. In addition, you get introduced to PyTorch, getting exposed to all those sophisticated libraries that help the reader learn how to maximize their compute power. I would say it is not intimidating at all even if you have not used PyTorch before. I would recommend this book to anybody seeking a textbook that is both easy to read and modern in its content. If were to rate the book I will give it a 10/10 as it really applies to both beginners and experienced practitioners, covers all the concepts one needs to apply in their operations, and acts as a quick reference.
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Reviewed in the United States on March 1, 2022
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Gabe Rigall
Pawtucket, US
★★★★★ 5
Thorough Primer for Machine Learning and PyTorch
Format: Paperback
BLUF: A thorough primer for machine learning enthusiasts with plenty of theory to underscore its many practical examples. A definite must-have for anyone looking to add PyTorch to their machine learning tool belt. PROS: - Extremely thorough (if not comprehensive). I really appreciate that this book doesn't just thrust one into building models with PyTorch. It starts at the "beginning" and provides examples, theory, additional resources, and citations along the way. - Theory. Those whose calculus and linear algebra courses ended many years ago will appreciate (if not remember exactly) the mathematical theory and notation that accompanies almost every paragraph. This book gives one the opportunity to "dig deeper" or stay in the shallows until the notation stops. - Python. Rather than simply utilizing Scikit-Learn to illustrate concepts and introduce models, this book contains many sections where models (such as a Perceptron) are coded from the ground up so the reader can fully understand the underlying mechanics. Python enthusiasts will nerd out. Parents of small children might want to skip a few pages. - Graphs, charts, and graphics. There are plenty of places where a drier text might have foregone the use of graphs. This text does not. It does however refrain from overusing them. - PyTorch. This should be obvious from the title, but this text prioritizes PyTorch instead of TensorFlow. This is especially helpful for those looking for an alternative to Keras and TensorFlow as the PyTorch API is very user-friendly. CONS: - Almost too much code. This isn't a true "con" but anyone wanting to emulate or follow along with the examples would do well to get the digital edition so they can copy and paste. - Length and complexity. Anyone hoping for a "quick read" or a "quick start guide" will be disappointed. This book hovers somewhere between an undergraduate primer and a graduate-level text for length and readability. This is not to say that it's difficult to read, merely that there are other "quick start" / "practical" texts out there that cater more to a lay audience.
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Reviewed in the United States on February 26, 2022

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