SKU: 69850574355
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buy wildflower seeds Native Short Grass and Wildflower Seed Mix

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Description

buy wildflower seeds Native Short Grass and Wildflower Seed MixWhen we describe one of our native seed mixes as short, we typically mean 3 to 5 feet tall. Our Native Short Grass and Wildflower Seed Mix was designed as a native grass planting with native wildflowers mixed in that have bloom times ranging from spring through fall once established. Attract Monarch Butterflies with Common and Butterfly Milkweed. Watch birds eat Ox Eye Sunflower and Yellow Grey headed Coneflower seeds. Wild Bergamot is a bee magnet

When we describe one of our native seed mixes as short, we typically mean 3 to 5 feet tall. Our Native Short Grass and Wildflower Seed Mix was designed as a native grass planting with native wildflowers mixed in that have bloom times ranging from spring through fall once established.

Attract Monarch Butterflies with Common and Butterfly Milkweed. Watch birds eat Ox Eye Sunflower and Yellow/Grey-headed Coneflower seeds. Wild Bergamot is a bee magnet and Little Bluestem is the larval host plant for many butterflies and moths.

Some things to remember:

This mix of native grasses and wildflowers will take 2 to 3 growing seasons to fully establish. We do include annual wildflowers for color and foraging the first growing season.

This mix performs best in well-drained soils and will need at least 4 to 6 hours of sunlight a day.

Contains the following species:

Grasses:

Elymus virginicus - Virginia Wild Rye

Schizachyrium scoparium - Little Bluestem

Bouteloua curtipendula - Side-oats Grama

Wildflowers:

Chamaecrista fasciculata - Partridge Pea 

Echinacea purpurea - Purple Coneflower

Heliopsis helianthoides - Ox Eye Sunflower

Coreopsis lanceolata - Lanceleaf Coreopsis

Gaillardia aristata - Blanket Flower

Dalea purpurea - Purple Prairie Clover

Desmanthus illnoensis - Illinois Bundleflower

Rudbeckia hirta - Black-eyed Susan

Eryngium yuccifolium - Rattlesnake Master

Dalea candida - White Prairie Clover

Astragalus canadensis - Canadian Milk Vetch

Ratibida pinnata - Yellow / Grey-headed Coneflower

Asclepias syriaca - Common Milkweed

Monarda fistulosa - Wild Bergamot

Penstemon digitalis - Foxglove Beardtongue

Lespedeza capitata - Roundheaded Bushclover

Coreopsis tinctoria - Plains Coreopsis

Solidago rigida - Stiff Goldenrod

Aster laevis - Smooth Aster

Asclepias tuberosa - Butterfly Milkweed

Seed Info

Seed Packet covers 250 square feet (a 10 x 25 area) and will take up to three growing seasons to fully establish. Each packet will cover approximately 250 square feet.

PLS Lbs. Per Acre Broadcast = 15

PLS=Pure Live Seed

Pure Live Seed is a measure of viable seed stated as a percentage. It is the product of total germination times purity.

Example: 96% Germination x 93% Purity = 89% PLS

All of our native warm season grasses and seed mixes are sold PLS.

Broadcast seeding is the process of sowing seed by hand. The seeds are sprinkled into the soil and can be lightly raked to ensure germination.

This mix of native grasses and wildflowers typically grows to a height of 3 to 5 feet. Please note that each site is unique and that several factors can affect overall height. These factors include sunlight, hydrology and overall soil health.


Product Details

Flower Color: Green, Yellow, Purple, Pink, Orange, White

Height: 3 to 5 Feet

Light Requirements: At Least 4 to 6 Hours of Sunlight a Day

Soil Hydrology: Dry to Mesic Soils

Bloom Time: Spring through Fall

Plant Type: Annuals/Perennials

Attracts: Birds, Bees, Butterflies and Humans

Suggested USDA Planting Zones: 3-7

Product Code: NSGM03

Color Boosters

The native perennials in your mix do require some patience to establish, but for instant gratification consider adding any of these quick establishing annuals. They're perfect pollinator plants, too!

Indian Blanket

Partridge Pea 

Quick Growing Wildflowers Native Seed Mix 

Cover Crops and Seed Carriers

Do you need a cover crop?

Know where you sow! Add some Rice Hulls to your order!

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SKU: 69850574355

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William P Ross
Los Angeles, 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
Dallas, 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
A
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Amazon Customer
Draper, 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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