SKU: 39785088628
sun lamp for indoor plants

sun lamp for indoor plants Sun Patch | Grow light for indoor plants and seedlings

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Description

sun lamp for indoor plants Sun Patch | Grow light for indoor plants and seedlingsdescription the sun patch a full spectrum grow light for seedlings and indoor plants the sun patch raises strong seedlings and keeps your indoor plants thriving, right on your tabletop. No more pale, leggy seedlings stretching towards a window that never quite gives them enough. It delivers full, sun like light from day one, so plants grow sturdy stems, healthy roots and full, green foliage. It's a proper full spectrum grow light in a tidy tabletop

 

 

 

description

the sun patch | a full spectrum grow light for seedlings and indoor plants

the sun patch raises strong seedlings and keeps your indoor plants thriving, right on your tabletop. No more pale, leggy seedlings stretching towards a window that never quite gives them enough. It delivers full, sun-like light from day one, so plants grow sturdy stems, healthy roots and full, green foliage.

It's a proper full spectrum grow light in a tidy tabletop form, just as happy raising a tray of seedlings as it is giving a shelf of houseplants a boost through the darker months.

the kind of light plants thrive in

Plants grow best under light that behaves like the sun, and that's exactly what the sun patch gives them. It covers the wavelengths plants use to photosynthesise, so growth is stronger and leaves come in greener. A precision lens sits over every diode and focuses the light down onto your plants rather than spilling it across the room, so more of it reaches the leaves where it counts.

exactly the light they need, without the guesswork

Different plants want different amounts of light, and what they want changes as they grow. the sun patch lets you give each one exactly the right exposure, then set the timer and leave it. Your plants get steady, consistent light every day, even when you're away, so they grow healthy without you having to think about it.

made to sit happily in your home

Grow lights have a reputation for looking like lab equipment. the sun patch doesn't. Warm bamboo arms and a clean, compact body mean it looks at home on a kitchen counter or a side table rather than out of place. It sets up in minutes and barely takes up any room.

lighting specs

  • Controller settings8h on / 16h off, 12h on / 12h off, 16h on / 8h off
  • Brightness settings100%, 80%, 60%, 40%, 20%
  • Light spectrum660nm, 3000K, 4000K
  • Output2,000 lumens
  • Voltage24V
  • Wattage24W
  • Beam angle120 degrees
  • IP ratingIP20
  • Operating temperature-10°C to +40°C
  • Lifespan25,000 hours

Photosynthetic photon flux density (PPFD)

  • 5cm: 850 µmol/m²/s
  • 10cm: 540 µmol/m²/s
  • 20cm: 290 µmol/m²/s
  • 30cm: 200 µmol/m²/s

what's included

the sun patch comes with everything you need to get growing.

  • 1 × sun patch light panel
  • 1 × light controller
  • 1 × light shade
  • 1 × power adaptor
  • 1 × set of bamboo light arms, with screws and an Allen key
  • 1 × instruction manual

setup

Setting up the sun patch takes a few minutes. The video below walks you through it.

 

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SKU: 39785088628

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Carol
Whiting, 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.
Carnegie, 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
West Palm Beach, 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
Chelsea, 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
A
Verified Purchase
Amazon Customer
Louisville, US
★★★★★ 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

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