SKU: 45100878613

MRCOOL DIY 5th Gen Multi-Zone 4-Zone 55,000 BTU 22 SEER2 (6K + 6K + 12K + 24K) Ductless Mini-Split Air Conditioner and Heat Pump

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Description

MRCOOL DIY 5th Gen Multi-Zone 4-Zone 55,000 BTU 22 SEER2 (6K + 6K + 12K + 24K) Ductless Mini-Split Air Conditioner and Heat PumpMRCOOL DIY Multi Zone 5th Generation 55K BTU Four Zone Ductless Mini Split A Heating and AC System You Can Install By Yourself! Heat or cool up to five rooms with the MRCOOL DIY Multi Zone 55,000 BTU 22 SEER2 4 Zone Ductless Heat Pump Split System 9K + 9K + 9K + 12K. This DIY Series multi zone product features easy installation that requires no special tools or training. You'll save thousands of dollars on installation and you can get the amazing air

MRCOOL DIY Multi-Zone 5th Generation 55K BTU Four Zone Ductless Mini Split - A Heating and AC System You Can Install By Yourself!

Heat or cool up to five rooms with the MRCOOL DIY Multi-Zone 55,000 BTU 22 SEER2 4 Zone Ductless Heat Pump Split System - 9K + 9K + 9K + 12K. This DIY Series multi-zone product features easy installation that requires no special tools or training. You'll save thousands of dollars on installation and you can get the amazing air comfort of your dreams due to the condenser’s 48,000 BTU capacity. This units consists of four 9,000 btu air handlers (400 square feet) and one 12,000 btu (550 square feet). A heat pump by design, this ductless HVAC solution can run in reverse and pull in heat from the outdoors when in a heating mode. It comes with a 7 year compressor warranty, (Plus a limited lifetime compressor warranty), 5 year parts manufacturer warranty! 

MRCOOL DIY 5th Gen Multizone 55,000 BTU systems can support up to FIVE indoor units.

The MRCOOL DIY Multi-Zone 55,000 BTU 22 SEER2 4 Zone Ductless Heat Pump Split System - 9K + 9K + 9K + 12K units are super easy to install and require no special training or expensive specialty tools. The DIY system includes Quick Connect lines that are pre-charged with eco-friendly R-454B refrigerant. Due to the Quick Connect line set, you don’t have to hire an HVAC technician to complete the install. We also have simple video instructions on how to install a DIY Multi-Zone unit yourself!

The MRCOOL DIY Multi-Zone 55,000 BTU 22 SEER2 4 Zone Ductless Heat Pump Split System - 9K + 9K + 9K + 12K can cool through the Summer, heat through the Winter, and dehumidify through the wet seasons. Plus, you can quickly check the temperature of each room in your home from the easy to read digital display or from the MRCOOL Smart Controller mobile app. The display on the front of each indoor air handler unit can also display troubleshooting codes and alerts, so you are always aware of any issues with your system. Operate each unit wirelessly with either the included remote or with the MRCOOL Smart Controller app for Apple or Android devices. You also have the ability to control your mini-split unit with Amazon Alexa or Google Home.

The four MRCOOL DIY Multi-Zone air handlers included in this set provide directional control of the heated or cooled air. This distributes the air evenly so everyone in the room can stay comfortable. If you are in a situation that requires forced cooling, you can set your MRCOOL DIY System to manual with the button located on the right side of the unit under the front panel. In this emergency operation mode, you can test the cooling operation of your unit after installation or to complete a maintenance task.

In auto mode, each unit provides air for your home at your desired comfort level. Set your desired temperature, and the HVAC unit will determine how much heat or air conditioning is needed. You can also set this system to a drying function, which will continue to control the space’s air temperature while dehumidifying.

Use the sleep mode at night to save money on your utilities bills and use less energy. Sleep mode operates in an 8 hour window once turned on.

The MRCOOL DIY Multi-Zone 55,000 BTU 22 SEER four-Zone Ductless Heat Pump Split Air Conditioner System - 9K + 9K + 9K + 12K comes with many options, so you can customize your system based on your needs. Limit your energy usage and save money on your utility bill by using the system’s timer function. If your system begins to run low on refrigerant, an alert will appear on the easy-to-read display on the front of each air handler, letting you know there may be a leak. If you desire to keep a room quiet and minimize lighted alerts, you can mute each indoor unit. By muting the system, the buzzer for alerts will not sound and the LED lit display will turn off. Should the unfortunate event of a power outage occur, the MrCool system will automatically shut off and then back on with the same settings once power returns.

Easily maintain your MRCOOL DIY Multi-Zone 55,000 BTU 22 SEER Four-Zone Ductless Heat Pump Split Air Conditioner Unit with alerts and reminders. Any troubleshooting codes will appear on the front display and the user manual contains an index for common codes. Air filter cleaning alerts are automatic, and you can easily keep the minimal indoor units clean with a dry or damp cloth.

Features:

  • Easy DIY® Installation
  • "Pre-charged DIY®
  • Quick Connect Line Set"
  • Simple to Use
  • Multi-room Comfort
  • Energy Efficient DC Inverter
  • 100% Sealed System
  • Gold Fin® Condenser
  • Eco Safe R-454B Refrigerant
  • Smartphone App Controls
  • Lifetime Technical Support
  • Follow Me® Feature
  • Low Ambient Cooling
Shipping Notes
  • Free Standard Shipping on $100+ Orders to the USA.
  • Except Preorder products are shipped in 48 hours.
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Exchange/Return Notes
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  • Final sale items are not eligible for returns or exchanges.
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SKU: 45100878613

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4.4 ★★★★★
Based on 9 reviews
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Verified Purchase
Par
Grantham, 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.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on December 20, 2024
R
Verified Purchase
Richard Hackathorn
Waukegan, 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.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on February 26, 2022
A
Verified Purchase
Amazon Customer
San Leandro, 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
Verified Purchase
Kindle Customer
Carnegie, US
★★★★★ 5
Very useful book
Format: Paperback
I use it for the machine learning class I teach.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on May 3, 2026
T
Verified Purchase
Tommy Jonsson
Carnegie, US
★★★★★ 5
Cover many areas in detail and recommendations for more to read for what's outside
Format: Paperback
Good book!
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on May 4, 2026

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