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Description
Code One Battery Operated Carbon Monoxide DetectorThe Code One Battery Operated Carbon Monoxide Alarm is intended for continuous monitoring of carbon monoxide levels. The alarm features a piezoelectric horn that is rated at 85 dB at 10 ft. The alarm is battery operated for uninterrupted monitoring, even during power outages, and runs on 2 AA batteries, which are included. Use to help provide continuous monitoring of carbon monoxide levels Piezoelectric horn is rated at 85 dB at 10 ft. Alarm will not
The Code One Battery-Operated Carbon Monoxide Alarm is intended for continuous monitoring of carbon monoxide levels. The alarm features a piezoelectric horn that is rated at 85 dB at 10 ft. The alarm is battery operated for uninterrupted monitoring, even during power outages, and runs on 2 AA batteries, which are included.- Use to help provide continuous monitoring of carbon monoxide levels
- Piezoelectric horn is rated at 85 dB at 10 ft.
- Alarm will not sound if carbon monoxide levels are below 30 PPM
- Battery operated for uninterrupted monitoring during power outages
- Test/reset button tests the unit for proper operation and resets the alarm
- Operated by 2 AA batteries (included)
- Compatible with Kidde, FireX, Code One, and Sentinel products
- Note: product may vary by store
- Carbon monoxide detector utilizes an electrochemical sensor to detect fire hazards and sounds an 85 db alarm when a hazard is detected
- UL/CSFM Ref. Kidde Part KN-COB-LP2
Features
| Item Weight | 0.5 |
| Alarm Type | Carbon Monoxide |
| Connector/Contact Type | None |
| Fixed or portable | Fixed |
| Voltage (volts) | 3 |
| Pack Size | 1 |
| Commercial/Residential | Residential |
| Included | Batteries |
| Returnable | 180-Day |
| Power Source | Battery |
| Alarm/Detector Features | Hush Feature |
| Battery Type Required | AA |
| Product Depth (in.) | 1.5 |
| Product Width (in.) | 4.5 |
| Product Height (in.) | 2.75 |
| Certifications and Listings | UL Listed |
Shipping Notes
- Free Standard Shipping on $100+ Orders to the USA.
- Except Preorder products are shipped in 48 hours.
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- Standard Shipping : 3-10 business days
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Exchange/Return Notes
- We offer a 30-day return/exchange service after receiving.
- Final sale items are not eligible for returns or exchanges.
- To process your return/exchange, please contact us at [email protected]
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4.1 ★★★★★
Based on 13 reviews
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Product Reviews
★★★★★ 5
Before GPT can chat, it has to learn.
Format: Paperback
One of the most comprehensive guides to AI and deep learning available. All concepts covered clearly and concisely with illustrations. Complex concepts are broken down into understandable terms. Even though ML and AI require some complex math, you won’t need it to get idea of what’s going on inside the computer’s “brain”.
I use this as a reference when teaching AI concepts and preparing presentations.
I highly recommend it
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on April 5, 2025
★★★★★ 5
Great examples and practical explanations
Format: Paperback
Excellent book. Highly recommend
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on May 19, 2025
★★★★★ 5
Great for intuitive understanding
Format: Paperback
Amazing book. Great examples and diagrams. If you're looking to get an intuitive grasp of deep learning, look no further. If you're an engineer looking to apply it, I would recommend pairing this with one of the more technical canonical texts and a programming focused book.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on May 4, 2024
★★★★★ 5
Taught me backpropagation
Format: Paperback
I'm finding this book a great reference to supplement Syracuse IST 691 Deep Learning in Practice. In particular, its explanation of backpropagation is the clearest I have found yet, and that even includes 3 Blue 1 Brown, which always does excellent explanations.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on April 13, 2025
★★★★★ 5
An Easy Read
Format: Paperback
A good narrative description of how the various systems work. Good for getting a conceptual understanding. No math to speak of, and if you want it, you can refer to the references cited, or your other favorite machine learning book.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on May 7, 2024
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