SKU: 58321020562
bird's nest fern houseplant

bird's nest fern houseplant Bird's Nest Fern 'Nidus' – Elegant Low-Maintenance Indoor Plant

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Description

bird's nest fern houseplant Bird's Nest Fern 'Nidus' – Elegant Low-Maintenance Indoor PlantBirds Nest Fern Nidus A Lush Green Statement for Any Space The Birds Nest Fern Nidus (Asplenium nidus) is a must have for anyone looking to bring a touch of the tropics into their home. With its striking, wavy fronds that unfurl like vibrant green ribbons, this fern is a living work of art. Its unique rosette shape resembles a cozy birds nest (hence the name), making it a standout in any plant collection. Picture it nestled on a bookshelf, perched on

Bird’s Nest Fern ‘Nidus’

A Lush Green Statement for Any Space

The Bird’s Nest Fern ‘Nidus’ (Asplenium nidus) is a must-have for anyone looking to bring a touch of the tropics into their home. With its striking, wavy fronds that unfurl like vibrant green ribbons, this fern is a living work of art. Its unique rosette shape resembles a cozy bird’s nest (hence the name), making it a standout in any plant collection.

Picture it nestled on a bookshelf, perched on a side table, or stealing the show as a floor plant in a decorative pot. Its bold, glossy foliage adds structure and energy to your space, while its clean lines complement a modern or boho aesthetic. Plus, the Bird’s Nest Fern thrives in humidity, making it a perfect companion for bathrooms, kitchens, or sunrooms.

What Makes It Special:

  • Visually Unique: The wide, crinkled fronds fan out like a nest, adding bold texture and lush color.
  • Low Maintenance: Thrives in indirect light and only needs watering when the soil is slightly dry.
  • Humidity Lover: A natural fit for bathrooms or kitchens where it will thrive with minimal effort.
  • Air-Purifying Bonus: Known for its ability to help improve air quality, it’s both functional and beautiful.

This fern’s elegant simplicity makes it perfect for any space, whether you’re curating a serene indoor jungle or just need a standout accent plant. Plus, its fuss-free nature means it will reward even beginner plant parents with long-lasting beauty.

Plant Details

  • Mature Height: 2–3 feet
  • Mature Width: 2–3 feet
  • Sun Exposure: Bright, indirect light; tolerates low light
  • Botanical Name: Asplenium nidus
  • Other Common Names: Bird’s Nest Fern, Nidus Fern

The term "nidus" comes from the Latin word for "nest," which aligns with the plant's distinctive rosette shape, resembling a bird's nest. Scientifically, Bird's Nest Ferns belong to the genus Asplenium—with Asplenium nidus being one of the most well-known species. These ferns are loved for their bright green, wavy-edged fronds and their ability to thrive in indirect light and humid conditions.

The Bird’s Nest Fern ‘Nidus’ is more than just a houseplant—it's a vibrant centerpiece that brings life and elegance to any room. Whether you're a seasoned plant enthusiast or just starting your green journey, this fern offers effortless beauty and charm with its lush, architectural fronds and air-purifying qualities. Its adaptability to various indoor environments and its low-maintenance care make it a delightful addition to your home. Elevate your space with the timeless appeal of the Bird’s Nest Fern and enjoy the tranquil, tropical vibe it effortlessly creates.

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SKU: 58321020562

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Hashi Hanta
Lowell, 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
Chelsea, 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.
Chelsea, 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
Bozeman, 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
Lexington, 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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