SKU: 91038361450
dark knight plant philodendron

dark knight plant philodendron White Knight Philodendron Rare Plant (Philodendron erubescens) – Jungle Relics

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Description

dark knight plant philodendron White Knight Philodendron Rare Plant (Philodendron erubescens) – Jungle RelicsThe White Knight Philodendron is a rare and striking plant that brings a touch of elegance to any indoor space. With its dark green leaves adorned with bold white variegation, its a living work of art that stands out in any plant collection. Perfect for both new plant enthusiasts and seasoned collectors, this low maintenance beauty adds a sophisticated, tropical vibe to your home. Why the White Knight is Considered Rare: The White Knight Philodendron

The White Knight Philodendron is a rare and striking plant that brings a touch of elegance to any indoor space. With its dark green leaves adorned with bold white variegation, it’s a living work of art that stands out in any plant collection. Perfect for both new plant enthusiasts and seasoned collectors, this low-maintenance beauty adds a sophisticated, tropical vibe to your home.

Why the White Knight is Considered Rare:

The White Knight Philodendron is considered rare and highly sought after among plant enthusiasts. Its unique variegation, featuring dark green leaves with striking white splashes, is a result of genetic variation that isn’t commonly found in many philodendron varieties. The combination of its rarity and stunning appearance makes it a prized addition to any plant collection.

Availability is often limited, which adds to its allure, and it may command higher prices compared to more common philodendrons. Its status as a rare plant makes it even more special for collectors or those looking to add a unique touch to their indoor garden.

Why You’ll Love It:

  • Rare Elegance: Its unique white-splashed leaves create a stunning visual contrast, elevating your indoor décor.
  • Easy to Care For: Adaptable and forgiving, the White Knight is ideal for plant lovers at any skill level.

Plant Care FAQs:

  • Plant Type: Chill
  • Plant Family: Araceae
  • Soil Type: Prefers a well-draining potting mix rich in organic matter. Add perlite or coco coir to improve aeration.
  • Soil pH: Enjoys neutral to slightly acidic soil (pH 6.0–7.0).
  • Watering: Allow the top inch of soil to dry out between waterings. Use a pot with drainage holes to avoid waterlogged roots.
  • Humidity Requirements: Thrives in moderate humidity (50%+). Use a pebble tray or humidifier to boost levels if needed.
  • Fertilizer: Feed monthly in spring and summer with a balanced, water-soluble fertilizer. Reduce feeding in fall and winter.
  • Special Care: Gently wipe leaves with a damp cloth to maintain their shine and health. Rotate the plant occasionally for even growth.

Pro Care Tip: Propagate the White Knight easily by cutting a stem with a node and rooting it in water or soil. This is a perfect way to share this rare gem with friends or expand your own collection.

Plant Styling Tips: The White Knight Philodendron’s striking variegation makes it a showstopper in any space. Style it in a sleek, neutral planter to highlight its bold foliage, or place it on a plant stand for added height and dimension. For a softer look, let its leaves cascade from a hanging pot or shelf, or encourage upward growth with a moss pole for a sculptural statement. Position it near a bright, indirect light source to emphasize its white splashes, and pair it with complementary plants or natural décor elements like woven baskets or ceramic pots for a cohesive, organic feel. Whether as a standalone centerpiece or part of a tropical collection, the White Knight adds elegance and charm to any room.

Tea Pairing: Enhance the serene ambiance of your White Knight with a cup of calming Chamomile Tea. The warm, golden hue and floral aroma of chamomile harmonize beautifully with the plant’s cool green and white tones, creating a relaxing, nature-inspired moment in your day.

Whether styled in a decorative pot or allowed to climb, the White Knight makes a captivating statement with its distinctive foliage and graceful growth.

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SKU: 91038361450

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4.1 ★★★★★
Based on 13 reviews
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William P Ross
New York, US
★★★★★ 5
Comprehensive Look At An Incredibly Complex Topic
Format: Hardcover
Deep Learning is an advanced book with great explanations and details. There is a heavy math focus with the book's beginning chapters detailing the necessary linear algebra and probability that one will need to understand deep learning. I liked that the author's chose to cover only the parts of these subjects which are relevant to deep learning. There are many interesting philosophical sections in the book as well. Just about when I was feeling overwhelmed with the complexity of the mathematics the authors take a step back and cover the foundations of deep learning such as borrowing concepts from human learning. There was an interesting dicussion about the early studies done on the vision of cat's and monkey's in the 1970s. The text covers the entire history of deep learning and the bibliography is hundreds of sources. It is clear this is the most comprehensive text available about deep learning. For anybody interested in this topic this book is a mandatory read. There are sections about machine learning as well, which makes sense because deep learning is a subset of machine learning. These sections focused on the machine learning concepts which are most relevant to deep learning. The book was well organized and divided into three parts which cover mathematics related to deep learning, typical deep learning techniques, and then more experiment learning techniques. Often the author's state when a technique works well or when it does not, and which types of data works best for the technique. Just a warning, the math in this book is highly complex. It requires a lot of work to go through this book, but the effort will be well rewarded.
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Reviewed in the United States on March 15, 2017
A
Verified Purchase
Adam
Los Angeles, US
★★★★★ 4
Too Dry.
Format: Hardcover
This was a required textbook for my class in college. I think it was too dry. The book titled Deep Learning: From Curiosity To Mastery is much more approachable.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on May 22, 2026
A
Verified Purchase
Amazon Customer
Natrona Heights, US
★★★★★ 5
Comprehensive! The Bible of Deep Learning!
This book has by far surpassed my expectations! I have purchased many machine learning and deep neural network books in the past, but nothing has ever come close to this book! First of all, it is written by the fathers of Deep Learning, and is therefore an authority. Secondly, the book is broken into three parts: 1. A math overview and refresher. 2. Deep Learning applications and 3. Research in Deep Learning. I can't help but go through this book from front to back. It is a smooth read, and every sentence written is meaningful. These guys know their stuff! And after you read this book, YOU WILL ALSO know your stuff! If you feel daunted by the price, just remember, you get what you pay for! I'd say they could easily charge about $300+ for this book, but they are doing everyone a very kind favor by ONLY charging this reasonable amount. You get A LOT of bang for your buck with this purchase. I hesitated at first about buying this book because of the price, but I am soooooo happy that I did! Worth every penny! Look no further, get this book and start your Deep Learning journey!!
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Reviewed in the United States on July 14, 2017
M
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mackster
Lowell, US
★★★★★ 1
A rushed, poorly written guide of how the "experts" can't really explain what Deep Learning is
Format: Hardcover
This book, in every sense of the word, is rushed. I think the authors wanted to establish themselves as leaders of this young-ish field, but does so by sacrificing quality. It also shows that Deep Learning theory has been there for a long time, known by another name called Neural Networks. The interesting algorithms are of MLP, Back Propagation and the classical neural networks. The optimization methods such as Adam are the ones that are new and interesting, and the only ones worthy of in this book. So, essentially, what you get from this book is use A for X, B for Y and C for Z type of dry, un-intuitive, badly written waste of paper. As for the structure of the book, it's like an example of how not to structure a book. It has some linear algebra, probability at the start (not good enough, and confuses more people and wastes paper). Goes on to prove other algorithms such as PCA (yeah, ok!). Then, talks about how this architecture works for this and that architecture. So, yeah, if you really want to try out deep learning, don't buy this book. Set up Tensorflow/pytorch/ other library, run the tutorials, find an architecture for the problem you are interested in and start tweaking that. You will have far more fun and would have saved your money. The praise that this book gets is beyond me. Did Musk even read this book? I doubt it.
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Reviewed in the United States on May 15, 2018
S
Verified Purchase
Stergios Papadimitriou
Battle Creek, US
★★★★★ 5
The classic textbook on Deep Learning
Format: Hardcover
Deep Learning is the promising direction towards general purpose effective artificial intelligence. There is an explosion of fruitful research in recent years and a lot of applications pursued mainly from technology giants as Google, Amazon, etc. and outstanding research institutions. The book "Deep Learning " by Ian Goodfellow, Yoshua Bengio, Aaron Gourville, is an excellent piece of work. They manage to present rather difficult things in an understandable manner. The theoretical presentation is outstanding typical of "classic" books. Also, the book stays close to the practical applicability of all the methods and discusses applications extensively. There are a lot of other useful books on deep learning that follow a more practical approach by focusing on a particular deep learning software package, but this one book is certainly much more essential since it provides the required theoretical background in order to be able to do serious work on deep learning. I consider the book as "must have" for anyone that works on deep learning either in an academic or in an industrial environment.
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Reviewed in the United States on August 25, 2018

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