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Description
dramatic philodendrons Black Gold Philodendron – Plant DetectivesBlack Gold Philodendron (Philodendron melanochrysum) Black Gold Philodendron is a dramatic climbing houseplant prized for its velvety, dark foliage that looks instantly high end. It is a great choice if you want a statement plant that feels lush and architectural, especially when trained up a pole. With bright, indirect light and steady care, it rewards you with larger leaves and stronger color over time. If you want a collector style philodendron
Black Gold Philodendron (Philodendron melanochrysum)
Black Gold Philodendron is a dramatic climbing houseplant prized for its velvety, dark foliage that looks instantly high-end. It is a great choice if you want a statement plant that feels lush and architectural, especially when trained up a pole. With bright, indirect light and steady care, it rewards you with larger leaves and stronger color over time. If you want a collector-style philodendron that still fits into an approachable routine, Black Gold Philodendron is a standout.
Distinctive Features
This philodendron is known for elongated, heart-shaped leaves with a rich, velvet texture and prominent lighter veining that creates a glowing contrast against the dark surface. As a climber, it produces larger, more impressive foliage when given a moss pole or support and encouraged to grow upward. Mature leaves can become quite large indoors under good conditions, creating a bold vertical display. The combination of velvety texture, deep color, and dramatic scale makes it one of the most striking foliage plants for indoor collections.
Growing Conditions
- Sun: Bright, indirect light is ideal, and avoid harsh direct sun that can scorch leaves.
- Soil: Airy, well-drained aroid mix that holds some moisture but never stays soggy.
- Water: Water when the top 1 to 2 inches of soil dry, and do not let the pot sit in water.
- Humidity: Moderate to higher humidity supports best leaf size and velvet texture, with average home humidity acceptable.
- Growth Habit: Climbing vine that benefits from a support pole for larger leaves and a fuller vertical form.
Ideal Uses
- Focal Point: Train up a moss pole to create a tall, dramatic centerpiece with velvety foliage.
- Bright Room Corner: Place in a bright corner to add depth, contrast, and a lush tropical feel.
- Plant Stands: Set on a stand so leaf texture and veining are visible at eye level.
- Collector Displays: Pair with other aroids to build a layered indoor jungle with contrasting leaf finishes.
Low Maintenance Care
- Watering: Keep evenly moist but not wet, and allow a partial dry-down between waterings.
- Support: Provide a moss pole and secure stems, keeping the pole lightly moist if you want faster climbing.
- Feeding: Feed monthly in spring and summer with a balanced houseplant fertilizer at a moderate strength.
- Leaf Care: Dust gently with a soft cloth and avoid harsh wiping that can damage velvety leaves.
Why Choose Black Gold Philodendron?
- Velvety Dark Leaves: Rich texture and deep color create a premium, dramatic look indoors.
- Gold Veining Contrast: Prominent veins add glow and definition across each leaf.
- Climbing Statement: Trained growth on a pole produces larger leaves and a stronger vertical display.
- Collector Appeal: A standout aroid that elevates any indoor plant collection.
Black Gold Philodendron is a great choice when you want a climbing plant with serious visual impact. Give it bright, indirect light, an airy mix, and steady moisture with good drainage, and it will reward you with larger, more dramatic leaves over time. With a support pole and consistent care, it becomes a lasting focal plant that transforms the feel of a room.
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4.5 ★★★★★
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Product Reviews
★★★★★ 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
★★★★★ 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
★★★★★ 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
★★★★★ 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
★★★★★ 4
Just learning it
Format: Paperback
Nice learning book just have to finish it
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Reviewed in the United States on December 10, 2025