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Description
nootka rose seeds Nootka Rose (Rosa nutkana) – Sparrowhawk Native PlantsRosa nutkana Nootka rose is an upright, thicket forming, deciduous shrub with unrivaled wildlife value. Large, sweet scented pink flowers appear at the branch tips in mid to late spring. These attractive flowers mature into summer fruits, called hips, that are highly nutritious in tea and eaten by countless species of birds and mammals, especially in the winter months when other foods are scarce. Plant type canopy layer: deciduous, large shrub Size at
Rosa nutkana
Nootka rose is an upright, thicket-forming, deciduous shrub with unrivaled wildlife value. Large, sweet-scented pink flowers appear at the branch tips in mid-to-late spring. These attractive flowers mature into summer fruits, called hips, that are highly nutritious in tea and eaten by countless species of birds and mammals, especially in the winter months when other foods are scarce.
- Plant type/canopy layer: deciduous, large shrub
- Size at maturity: 4-10' tall, 2-3' wide
- Light requirements: full sun, part sun/part shade
- Moisture requirements: dry to wet soil
- Bloom time: April - August (April - May in the Portland Metro area)
- Growth rate/ease: fast growing, easy to grow
- Wildlife support: leaves/twigs are a food source for squirrels, beavers, porcupines, deer, elk, moose, caribou and bighorn sheep; young shoots are also popular with aphids which in turn provide food for a wide range of predators including ladybugs and songbirds; flowers attract and provide nectar for hummingbirds, adult butterflies and bees and are well-known as “deer candy”; hips provide food to several bird and mammal species including grouse, bluebirds, juncos, grosbeaks, quail, pheasants, and thrushes - plus chipmunks, rabbits, hares, porcupines, coyotes, deer, elk, and bear; seeds are used by birds as a source of grit; the overall plant attracts and supports predatory and other beneficial insects and is a caterpillar host plant and larval food source for several species of native bees and butterflies including mourning cloak butterfly; thickets provide critical shelter and habitat for birds such as pheasants and grouses
- Native habitat/range: locally common in thickets, riparian areas, along forest edges, and on rocky slopes from Alaska to California, and east to the Rocky Mountains. Portland Plant List - yes.
- Special features & uses: bird and wildlife favorite; fragrant flowers; landscape uses include pollinator gardens, raingardens, habitat hedgerows; traditionally used medicinally by many indigenous groups in the Pacific Northwest (including the Bella Coola, Cowichan, Lummi, Nlaka'pamux, and others), an infusion of roots and sprouts can be used as eyewash, decoction of bark can be used in tea to ease labor pains during childbirth and as a hair/body wash, poultice of chewed leaves eases bee stings, decoction of roots can treat sore throats, decoction of branches treats diarrhea and vomiting, poultice of ashes can heal skin swellings; young shoots are edible raw, boiled, dried, made into a jam or tea, and used as a spice, hips can be made into a delicious tea, exceptionally high in vitamins A, C & E; roots can be used to make reef nets, branches for hand brooms, to remove human scent before hunting and are believed by some to bring good luck; dried flower petals make excellent potpourri
Gardening with Nootka Rose: Nootka rose is a gorgeous wildlife magnet that prefers full to partial sun and tolerates most types of soils - including drought and seasonal wetness! That said, it is aggressive and eventually forms large, impenetrable thickets over time. It is valuable for stabilizing banks, especially along streams and is ideal for colonizing large spaces and habitat-friendly hedgerows where space allows.
Photo Credit 1 (flower close-up): © John Brew, some rights reserved (CC-BY-SA)
Photo Credits 2, 4-6 (branch with buds, flower with bug, branches in the garden): Karli Del Biondo, Beetles and Bees
Photo Credit 3 (with bee): "Rosa nutkana" by Jeffrey Lee (he/him/his) is marked with CC0 1.0.
Photo Credit 7 (hips on branches): © 66dodge, some rights reserved (CC-BY)
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4.6 ★★★★★
Based on 22 reviews
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Product Reviews
★★★★★ 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
★★★★★ 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