SKU: 16492590221
english ivy indoor plant

english ivy indoor plant English Ivy | Hedera helix

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Description

english ivy indoor plant English Ivy | Hedera helixElevate your indoor space with the timeless elegance of English Ivy (Hedera helix), a botanical masterpiece that will captivate plant enthusiasts and collectors alike. Each meticulously chosen specimen, hand picked for its exceptional beauty and vitality by the discerning team at Happy Houseplants, serves as a testament to the enchanting allure of nature. English Ivy, known for its cascading foliage and classic charm, adds a touch of sophistication to

Elevate your indoor space with the timeless elegance of English Ivy (Hedera helix), a botanical masterpiece that will captivate plant enthusiasts and collectors alike. Each meticulously chosen specimen, hand-picked for its exceptional beauty and vitality by the discerning team at Happy Houseplants, serves as a testament to the enchanting allure of nature.

English Ivy, known for its cascading foliage and classic charm, adds a touch of sophistication to any indoor oasis. Its lush green leaves create a serene ambience, inviting admiration and reverence with their graceful presence.

Originating from Europe and Western Asia, English Ivy thrives in various climates, making it an ideal choice for indoor cultivation. Whether displayed as a trailing accent or trained to climb along trellises, this versatile plant effortlessly adapts to its surroundings, bringing a sense of timeless beauty to your home.

Caring for English Ivy is straightforward and rewarding:

Light Requirements: English Ivy thrives in moderate to bright indirect sunlight. Place it near a window with filtered light to promote healthy growth and vibrant foliage.

Temperature and Humidity: Maintain room temperatures between 15°C and 24°C (59°F and 75°F) and moderate humidity levels. Avoid placing the plant near drafty areas or heating vents.

Watering: Keep the soil consistently moist but not waterlogged. Allow the top inch of soil to dry out between waterings, and water thoroughly when needed. During the growing season (spring and summer), increase watering frequency, and reduce it in the dormant season (fall and winter).

Soil and Potting: Plant your English Ivy in well-draining potting mix rich in organic matter. Consider adding perlite or sand to improve drainage. Repot the plant as needed to accommodate its growth.

Fertilizing: Feed your English Ivy with a balanced liquid fertilizer diluted to half strength every four to six weeks during the growing season. This will support healthy growth and lush foliage.

Size: 13cm full pot (fast grower!)

Styling with English Ivy offers endless possibilities:

Hanging Beauty: Showcase English Ivy in a hanging basket or macramé planter, allowing its cascading foliage to create a captivating display.

Climbing Elegance: Train English Ivy to climb along trellises, shelves, or walls, adding a touch of natural beauty to vertical spaces.

Tabletop Charm: Place English Ivy in decorative pots or terrariums to create charming tabletop displays, perfect for adding a refreshing touch to any room.

Our English Ivy plants are hand-picked for their exceptional beauty and vitality, arriving in pristine condition and ready to enhance your indoor sanctuary. Immerse yourself in the captivating world of English Ivy and experience the timeless beauty of this botanical treasure.

All plants are supplied in plastic nursery pots.

 

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SKU: 16492590221

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Hashi Hanta
San Leandro, US
★★★★★ 5
Excelllent book
Format: Hardcover
As one of the group of Native Americans who landed on Alcatraz with Richard Oakes, I enjoyed this book. Richard was a fantastic man. A good man.
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Reviewed in the United States on February 14, 2019
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Carol
Belleville, US
★★★★★ 5
Need to read book
Format: Hardcover
The truth about the Native people. THANK YOU Kent for writing this book. We purchased about 12 total.
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Reviewed in the United States on November 24, 2019
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Walter Echo-Hawk, author of THE SEA OF GRASS.
Natrona Heights, US
★★★★★ 5
Native American history at its best!
Format: Hardcover
Kent Blansett's engrossing story about the life & times of the famed Mohawk activist Richard Oakes is Native American history at its best. I appreciated the well-written context provided about the birth, growth and impact of the Red Power Movement and the pivotal role that social justice activism played in the rise of modern Indian nations in the United States today. This scholarly work helps us understand modern Native America and is a "must-read" for every Native American Studies student and scholar, as well as readers interested in important American social justice movements.
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Reviewed in the United States on April 1, 2019
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Par
Lowell, US
★★★★★ 5
Excellent book on ML
Format: Paperback
This is a great book on machine learning. Topics covered are extensive - from beginner level to advanced topics including math behind different algorithms. However, not "all" algorithms are covered. Please go through the table of contents. The first part - 11 chapters - covers machine learning concepts and second part covers advanced topics with Pytorch. There are lots of excellent code and they work!! The quality of the book I received is excellent. I have gone through all 742 pages, and it has held up very well!! I used Jupyter notebook to run all examples. I created a new notebook and copied and pasted the code and ran them. This approach worked very well for me. At the same time, I could experiment with my take on the code snippets and definitely added to my knowledge. Only issue I have is on the second part of the book discussing PyTorch: (1) Some packages are a bit older version: e.g., transformer 4.9.1 whereas current version is 4.48+. It took some tweaking/recoding to get the examples working. (2) There is not much discussion on why certain architecture was chosen - e.g., number of layers, is there a rule of thumb on how to improve performance by changing these parameters? Even with CUDA the code run for a long time. Therefore, experimenting with different values of parameters become too time consuming. (3) On the same note, if I can achieve test accuracy of 90%+ using logistic regression and almost the same (perhaps one or two percent better with PyTorch with IMDB movie review dataset and that two much faster why should I use PyTorch for this dataset? Obviously, PyTorch is for certain types of problems. Discussions can be included by not adding to the exhaustive (and apt) contents. Personally I was disappointed by lack of any example on time series. Must have for ML practitioner as a reference and guide.
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Reviewed in the United States on December 20, 2024
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Richard Hackathorn
Lake Worth, US
★★★★★ 5
Excellent Textbook for Hands-On Learning of ML
Format: Kindle
This textbook is for the serious life-long learners of machine learning. There are at least two ways to ‘consume’ this book. For the expert in ML, this is a textbook to study as a clear comprehensive ML overview and then to dive into sections of interest or ignorance. The concepts are grounded in code examples and are well cited (with links) to sources. Further, this textbook is appropriate if you are TensorFlow-centric and want to broaden into cutting-edge ML models/tools coded in PyTorch. For a new learner to ML, this is a textbook to DO (not just READ) with hands-on and brain-engaged. If you realize that ML is a key life-long skill for your career, consider this textbook as part of a daily learning habit (10-30 min). From personal experience, my advice to the new learner is as follows… First, clone the GitHub repository, setup your Python environment, and study the textbook, while working through the notebooks. Go on tangents and break the code. Do this methodically as part of your daily learning habit, but do not hesitate to jump ahead several chapters to prepare for tomorrow’s meeting. There is enough excellent material here for a full year of ML adventures. I did a similar strategy with Raschka’s first textbook. About four years ago, I had finished Andrew Ng’s Deep Learning Specialization as a student in his first cohort. I knew the concepts well but could not do the actual application coding. I was surprised how my Python coding improved by following Raschka’s clean and elegant style. And Raschka’s code examples were meaty enough to be springboards into working applications. Several textbook editions later, what is different about this new edition? First, it moves you through scikit-Learn (a firm foundation) to PyTorch, instead of TensorFlow. PyTorch is a better stepping-stone, both conceptually and practically. With PyTorch, you will go further with less energy, while being able to convert your efforts into TensorFlow as needed. In addition, most of the cutting-edge ML/AI/DL research is in PyTorch. It is nice to read a recent arXiv paper, clone their repository, click on the Colab tutorial, and replicate their experiments, along with picking up a ton of new coding tricks & tips. I am excited to work through these PyTorch sections to hone my skills. Second, there is a clear recognition of model tracking and tuning practices. This is often a gap in other ML textbooks and courses. Once you progress beyond the simple demo examples in a lecture, you realize that the real work is experiments, more experiments, and still more experiments, so that you must understand what the model architecture and hyperparameters are doing to your dataset. There is good coverage of scikit-Learn pipeline, grid search, model performance, and the like. Third, ML/AI/DL practice is rapidly evolving. Every week new ML packages/services become available that could save much grief on your current project. What is refreshing about Raschka’s textbook series is that he constantly adding cutting-edge topics because he likes to stay current and to help us stay current. Hence, this edition contains recent ML treats as: transformers, self-supervised learning, autoencoders-to-GAN, graph neural networks, DBSCAN, t-SNE (with brief mention of UMAP), and PyTorch-Lightning.
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Reviewed in the United States on February 26, 2022

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