SKU: 61620128478

SFP-10G-BX20D-I Cisco® Compatible Transceiver SFP+ 10GBase-BX-D (Tx1330nm/Rx1270nm, SMF, 20km, LC, DOM, Ind Temp)

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SFP-10G-BX20D-I Cisco® Compatible Transceiver SFP+ 10GBase-BX-D (Tx1330nm/Rx1270nm, SMF, 20km, LC, DOM, Ind Temp)SFP 10G BX20D I Cisco Compatible Transceiver SFP+ 10GBase BX D (Tx1330nm Rx1270nm, SMF, 20km, LC, DOM, Ind Temp) ATGBICS Cisco Compatible SFP 10G BX20D I SFP+ 10GBase BX form factor network transceiver supports a distance of up to 20km over single mode fibre (SMF) using a wavelength of 1330 1270nm via an LC Simplex connector. This product operates within an industrial temperature range. Digital optical monitoring (DOM) support is also present enabling

SFP-10G-BX20D-I Cisco® Compatible Transceiver SFP+ 10GBase-BX-D (Tx1330nm/Rx1270nm, SMF, 20km, LC, DOM, Ind Temp)

ATGBICS Cisco® Compatible SFP-10G-BX20D-I SFP+ 10GBase-BX form factor network transceiver supports a distance of up to 20km over single-mode fibre (SMF) using a wavelength of 1330/1270nm via an LC Simplex connector. This product operates within an industrial temperature range. Digital optical monitoring (DOM) support is also present enabling real-time monitoring of the parameters of the fibre optic transceiver.

Our product meets the specification of Cisco® SFP-10G-BX20D-I and we proudly offer a compatibility guarantee and limited lifetime warranty. Our rigorously tested products record a unique traceable serial number and are fully compliant with all MSA (Multi-Source Agreement) and IEEE standards & protocols.


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SKU: 61620128478

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MrGee
Battle Creek, US
★★★★★ 5
An enjoyable, and seriously excellent, path to understanding Deep Learning...
Format: Paperback
Deep Learning is changing our world. If you want to understand more, this is a great place to start. Andrew Glassner is a talented explainer - I took his short course on Deep Learning and learned so much, but also came away impressed at how well he can make complex material so clear and engaging. And this book is jammed packed with insights, visuals, and clear explanations. The author has a playful, sometimes quirky style that shines through, which gives this tour a lot of personality as well as information. Very enjoyable reading - I felt like he captured all that was good about his course (and then some) and bottled it up in this book. There is a lot more material here than in that course, and it is well laid-out and organized so that it is easy to roam around and come back to review the pieces that matter to you. Even if you plan to go to on to be a world-class Deep Learning engineer or mathematician, you have to start by understanding the concepts. And this book does a great job of presenting all the core ideas in a way that makes them clear and memorable.
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Reviewed in the United States on August 5, 2021
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R. Cote
Houston, US
★★★★★ 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
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Reviewed in the United States on April 5, 2025
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Rafael Azevedo Souza Costa
Boise, US
★★★★★ 5
Great examples and practical explanations
Format: Paperback
Excellent book. Highly recommend
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Reviewed in the United States on May 19, 2025
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Thomas
San Leandro, US
★★★★★ 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.
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Reviewed in the United States on May 4, 2024
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La Monte HP Yarroll
West Palm Beach, US
★★★★★ 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.
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Reviewed in the United States on April 13, 2025

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