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Description
is philodendron air purifier Philodendron Cordatum | Heartleaf Vining Houseplant | Low Light Air PurifierDescription Light Soil Water Hardiness The Philodendron Cordatum, also called Sweetheart Vine or Heart Leaf Philodendron, is a trailing houseplant native to Central America and the Caribbean. This easy care plant has glossy, heart shaped, dark green leaves that look stunning in different types of planters and hanging baskets. In its natural habitat, this plant climbs up trees in the forest canopy. It prefers indirect sunlight and can tolerate many
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The Philodendron Cordatum, also called Sweetheart Vine or Heart Leaf Philodendron, is a trailing houseplant native to Central America and the Caribbean. This easy-care plant has glossy, heart-shaped, dark green leaves that look stunning in different types of planters and hanging baskets.
In its natural habitat, this plant climbs up trees in the forest canopy. It prefers indirect sunlight and can tolerate many lighting conditions, including low-light shady spots. This makes Philodendron Cordatum a perfect houseplant for any home or office.
The Philodendron Cordatum, featured in NASA's Clean Air Study, effectively purifies indoor environments by eliminating formaldehyde.
The Philodendron Cordatum, with its heart-shaped leaves, is a popular Feng Shui plant. Its lush, green foliage symbolizes growth, vitality, and positive energy. The heart shape is associated with love, compassion, and harmony, making it a perfect choice for enhancing the emotional atmosphere of your home.
For the Cow Pot Option - These pots are 100% biodegradable and plantable, crafted entirely from composted cow manure to nourish your soil as they disappear.
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Philodendron Cordatum prefers bright, indirect sunlight, but it also tolerates different lighting conditions, including low-light shady spots. Too little light, however, can slow down its growth and makes this plant leggy. Avoid harsh direct sun to prevent scorching leaves.
Check the soil once per week and only water when the top 2" of the soil is dry to the touch. Water thoroughly and drain well after each watering. Crispy leaves mean that your plant needs more water, and yellow leaves indicate that it was over-watered. This plant needs less water if grown in medium or low light conditions.
This plant prefers well-drained, porous soils. It is recommended that you add some pertile to general houseplant potting soil to increase drainage.
This plant grows best in normal room temperatures (between 65°F-80°F). This plant is not frost-tolerant and it does not grow well when the temperature drops below 50°F. Philodendron Cordatum prefers high humidity (over 50%), so mist your plant and use a humidifier when the environment is too dry.
This plant should be fertilized once per month during the growing season (spring/summer) with diluted houseplant fertilizer. You can alternatively use a slow-release fertilizer twice per year.
This plant is mildly toxic if ingested, so keep it out of reach of pets and children. -
USDA Zone 10-12
USDA Zone 9b: to -3.8 °C (25 °F)
USDA Zone 10a: to -1.1 °C (30 °F)
USDA Zone 10b: to 1.7 °C (35 °F)
USDA Zone 11: above 4.5 °C (40 °F)
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4.1 ★★★★★
Based on 8 reviews
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Product Reviews
★★★★★ 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
★★★★★ 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
★★★★★ 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
★★★★★ 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
★★★★★ 5
100% Recommend
Format: Paperback
Invincible Compendium One completely lived up to the hype. From the very first chapter, I was hooked by the story, the action, and the character development. What starts off feeling like a classic superhero story quickly becomes something much deeper, darker, and way more emotional than expected.
The artwork is incredible and the fight scenes are intense without feeling repetitive. Every character feels important and layered, especially Mark and Omni-Man. The pacing is excellent for such a massive collection, and it’s hard to put down once you start reading.
If you’re a fan of superhero comics but want something with real stakes, shocking twists, and strong storytelling, this is absolutely worth reading. Easily one of the best graphic novels I’ve picked up in a long time.
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Reviewed in the United States on May 23, 2026