SKU: 74469214806
whipple way philodendron

whipple way philodendron Philodendron 'Whipple Way' – Foliage Factory

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Description

whipple way philodendron Philodendron 'Whipple Way' – Foliage FactoryPhilodendron 'Whipple Way' Philodendron 'Whipple Way' is a variegated climbing Philodendron with long, narrow leaves in green, cream, mint and pale speckled sections. Young plants start fairly slim, then develop a longer vine with visible nodes and aerial roots as they mature. Each leaf can look different. Some leaves show fine marbling, while others carry broader pale sections along the blade, giving Philodendron 'Whipple Way' a lighter, more

Philodendron 'Whipple Way'

Philodendron 'Whipple Way' is a variegated climbing Philodendron with long, narrow leaves in green, cream, mint and pale speckled sections. Young plants start fairly slim, then develop a longer vine with visible nodes and aerial roots as they mature.

Each leaf can look different. Some leaves show fine marbling, while others carry broader pale sections along the blade, giving Philodendron 'Whipple Way' a lighter, more elongated look than many common climbing Philodendron cultivars.

  • Growth habit: Climbing Philodendron with a lengthening vine and aerial roots.
  • Leaf shape: Long, tapered leaves with a smoother surface than many heart-leaved Philodendron cultivars.
  • Variegation: Cream to mint-white marbling, speckling and pale sectors on green leaves.
  • Support: A pole, plank or trellis helps mature leaves develop and keeps the vine easier to manage.

Whipple Way growth and support

Philodendron 'Whipple Way' grows from a central climbing stem. As the vine lengthens, aerial roots can attach to a textured surface, and the leaves usually sit more neatly when the plant is trained upward early.

Its long, pale variegated leaves can become easier to manage when the stem is guided upward before the vine hardens into a leaning position.

Care for Philodendron 'Whipple Way'

  • Light: Give bright filtered light. Direct midday sun can brown the pale sections quickly.
  • Support: Add a textured pole, plank or trellis while the stem is still flexible enough to guide.
  • Watering: Water thoroughly, then let the upper part of the mix dry before watering again. Cold, wet substrate can damage the roots and lower stem.
  • Substrate: Use an airy aroid mix with bark, coco chips, perlite or pumice so the roots receive moisture and oxygen.
  • Humidity: Moderate to higher humidity helps new leaves open with fewer dry edges.
  • Temperature: Keep it warm, ideally around 18–28 °C, and protect it from cold draughts.
  • Feeding: Feed lightly during active growth. Heavy fertiliser will not make very pale growth stronger.

Common Whipple Way problems

  • Brown pale sections: Check for harsh sun, dry air or irregular watering. Move the plant to gentler light and stabilise moisture.
  • Soft yellow leaves: Inspect the roots and lower stem. Improve drainage and let the mix dry further between waterings.
  • Small new leaves: Check light, roots and support. Weak growth often follows low light or a stressed root system.
  • Mostly white new growth: If several leaves in a row have very little green, prune back to a node with stronger variegation balance.
  • Sticky marks or stippling: Check petioles, leaf backs and new growth for thrips, scale or mites, then isolate and treat early.

Prune carefully because every leaf carries a different pattern. Remove damaged leaves when they are spent, but keep healthy green-and-cream leaves where possible.

Safety around pets and children

Philodendron 'Whipple Way' is not pet-safe. Like other Philodendron, it contains insoluble calcium oxalate crystals that can irritate the mouth, lips and throat if eaten. Keep cuttings and trimmed leaves away from pets and children.

Philodendron name background

Philodendron belongs to Araceae, the aroid family. The genus name comes from Greek roots meaning “loving” and “tree”, referring to the climbing habit seen in many species.

Philodendron 'Whipple Way' develops long, pale mint-cream leaves on a climbing stem with visible nodes and aerial roots.

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William P Ross
Whiting, 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
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Adam
Houston, 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.
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Reviewed in the United States on May 22, 2026
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Chelsea, 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
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mackster
Whiting, 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
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Stergios Papadimitriou
Lexington, 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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