SKU: 33455240948
palm tree dracaena

palm tree dracaena 10 DRAGON TREE Dracaena Draco Canary Island Drago Blood Asparagus Yucc – Seedville USA

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Description

palm tree dracaena 10 DRAGON TREE Dracaena Draco Canary Island Drago Blood Asparagus Yucc – Seedville USADESCRIPTION: NAME: Dragon Tree OTHER COMMON NAMES: Canary Islands Dragon Tree Drago Dragon Blood Tree SCIENTIFIC NAME: Dracaena Draco syn. Asparagus Draco Yucca Draco COLOR: Greenish White Cream Flowers Coral Orange Berries PLANT SEEDS: Outdoors after frost Indoors weeks before last frost BLOOM TIME: Late Winter Early Spring Early Summer HARDINESS ZONE: 9 11 PLANT HEIGHT: 15 25' PLANT SPACING: 15 15' LIGHT REQUIREMENTS: Sun Part Shade Houseplant SOIL

DESCRIPTION:

NAME: Dragon Tree

OTHER COMMON NAMES: Canary Islands Dragon Tree / Drago / Dragon Blood Tree

SCIENTIFIC NAME: Dracaena Draco syn. Asparagus Draco / Yucca Draco

COLOR: Greenish White - Cream Flowers / Coral - Orange Berries

PLANT SEEDS: Outdoors after frost / Indoors weeks before last frost

BLOOM TIME: Late Winter - Early Spring / Early Summer

HARDINESS ZONE: 9 - 11

PLANT HEIGHT: 15 - 25'

PLANT SPACING: 15 - 15'

LIGHT REQUIREMENTS: Sun - Part Shade / Houseplant

SOIL & WATER PREFERENCES: Average - Dry

QUANTITY: 10 Seeds

OTHER: The awe-inspiring Dragon Tree is native to the Canary Islands & a few surrounding locations. It is a very popular landscape ornamental in tropical regions, & as a patio & houseplant in cooler climates. This Dracaena is a Royal Horticultural Society's Award of Garden Merit winner.

The Dragon Tree is fairly slow growing, having a single trunk for the first 10 - 15 years of its life before branching out. Once they begin branching out, the branches will continue to split every 10 – 15 years. These long lived trees can survive for hundreds of years, repeating this process over & over to form an intricately patterned umbrella shape. While their average height is 15 – 25’, these trees can grow to be well over 25’ in time, & often develop aerial roots with age.

The foliage of this evergreen succulent is blue-green in color, & the sword-shaped leaves reach 2’ long. The Dragon Tree’s bark starts out smooth, becoming red-striped & scaly over time. If the leaves or bark are cut, they ooze a red resin called “Dragon’s Blood”, which has several traditional medicinal uses. The seeds may be poisonous - do not eat them. This red sap has also been used as a varnish & colorant since ancient times.

Depending on the climate it is grown it, the Dragon Tree’s fragrant blooms will appear between late winter & early summer. As the seasons progress, the flowers will turn to lovely coral colored berries. Being an island native, Dragon Trees are well suited to growing in the salty & windy conditions of coastal regions. They are also quite drought tolerant.

The Dragon Tree is listed on the International Union for Conservation of Nature List of Threatened Species Red List as Vulnerable, & it is a protected species in some places.



* We also have White & Purple Dragon Fruit seeds in our store! *



* FREE SHIPPING ON ALL ADDITIONAL SEEDS!

PAY ONE FLAT SHIPPING FEE PER ORDER NO MATTER HOW MANY PACKS OF SEEDS YOU SELECT!

WE HAVE OVER 2,000 TYPES OF FLOWER, VINE, TREE, SHRUB, HERB, FRUIT, & VEGETABLE SEEDS TO CHOOSE FROM!!!

Photo Credit: 3 By Zyance - Own work, CC BY-SA 2.5, httpscommons.wikimedia.orgwindex.phpcurid=1760459 cropped

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SKU: 33455240948

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Verified Purchase
Amazon Customer
Los Angeles, US
★★★★★ 4
Just learning it
Format: Paperback
Nice learning book just have to finish it
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on December 10, 2025
K
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Kindle Customer
Boise, US
★★★★★ 5
Very useful book
Format: Paperback
I use it for the machine learning class I teach.
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Reviewed in the United States on May 3, 2026
T
Verified Purchase
Tommy Jonsson
Grantham, US
★★★★★ 5
Cover many areas in detail and recommendations for more to read for what's outside
Format: Paperback
Good book!
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Reviewed in the United States on May 4, 2026
M
Verified Purchase
Moses Kayanda
Phoenix, US
★★★★★ 5
One of the best machine learning books...
Format: Paperback, Format: Paperback
Machine Learning can often be intimidating whether you are starting out or already a practitioner. It is easy to get stuck on one concept, walk away frustrated, or just copy that code you find on StackOverflow without really understanding what it does. What the authors of this book, Machine Learning with PyTorch and Scikit-Learn, have managed to do is to keep the reader engaged giving a deeper illustration as to how the concepts work. In this book, you get practical code examples, a detailed explanation of how the various library tools work, and exposure to the mathematical concepts behind machine learning algorithms. In addition, what I like about the book unlike many machine learning books is that the authors have managed to intuitively explain how each algorithm works, how to use them, and the mistake you need to avoid. I have not read a Machine Learning book that better explains Transformers as this one does. The authors have managed to give a detailed dive into this model architecture through well-explained codes and illustrations. As a reader, you walk away having intuitively grasped the concepts of attention and self-attention in ways that will make this crucial NLP architecture clear. You get exposed to pre-trained models from HuggingFace library which really helps to have that hands-on experience working with large datasets. As they have done throughout the book, the authors have broken down those complex mathematical operations into simple explanations that are easy to follow. What I generally like about the book is how it seamlessly connects all the chapters, not throwing off the reader. There are numerous external resources quoted throughout the book. This helps spark that curiosity to dig deeper. In addition, you get introduced to PyTorch, getting exposed to all those sophisticated libraries that help the reader learn how to maximize their compute power. I would say it is not intimidating at all even if you have not used PyTorch before. I would recommend this book to anybody seeking a textbook that is both easy to read and modern in its content. If were to rate the book I will give it a 10/10 as it really applies to both beginners and experienced practitioners, covers all the concepts one needs to apply in their operations, and acts as a quick reference.
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Reviewed in the United States on March 1, 2022
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Verified Purchase
Gabe Rigall
Chelsea, US
★★★★★ 5
Thorough Primer for Machine Learning and PyTorch
Format: Paperback
BLUF: A thorough primer for machine learning enthusiasts with plenty of theory to underscore its many practical examples. A definite must-have for anyone looking to add PyTorch to their machine learning tool belt. PROS: - Extremely thorough (if not comprehensive). I really appreciate that this book doesn't just thrust one into building models with PyTorch. It starts at the "beginning" and provides examples, theory, additional resources, and citations along the way. - Theory. Those whose calculus and linear algebra courses ended many years ago will appreciate (if not remember exactly) the mathematical theory and notation that accompanies almost every paragraph. This book gives one the opportunity to "dig deeper" or stay in the shallows until the notation stops. - Python. Rather than simply utilizing Scikit-Learn to illustrate concepts and introduce models, this book contains many sections where models (such as a Perceptron) are coded from the ground up so the reader can fully understand the underlying mechanics. Python enthusiasts will nerd out. Parents of small children might want to skip a few pages. - Graphs, charts, and graphics. There are plenty of places where a drier text might have foregone the use of graphs. This text does not. It does however refrain from overusing them. - PyTorch. This should be obvious from the title, but this text prioritizes PyTorch instead of TensorFlow. This is especially helpful for those looking for an alternative to Keras and TensorFlow as the PyTorch API is very user-friendly. CONS: - Almost too much code. This isn't a true "con" but anyone wanting to emulate or follow along with the examples would do well to get the digital edition so they can copy and paste. - Length and complexity. Anyone hoping for a "quick read" or a "quick start guide" will be disappointed. This book hovers somewhere between an undergraduate primer and a graduate-level text for length and readability. This is not to say that it's difficult to read, merely that there are other "quick start" / "practical" texts out there that cater more to a lay audience.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on February 26, 2022

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