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Siamese Network with Triplet Loss in Keras に戻る

Coursera Project Network による Siamese Network with Triplet Loss in Keras の受講者のレビューおよびフィードバック

4.6
109件の評価

コースについて

In this 2-hour long project-based course, you will learn how to implement a Triplet Loss function, create a Siamese Network, and train the network with the Triplet Loss function. With this training process, the network will learn to produce Embedding of different classes from a given dataset in a way that Embedding of examples from different classes will start to move away from each other in the vector space. This course runs on Coursera's hands-on project platform called Rhyme. On Rhyme, you do projects in a hands-on manner in your browser. You will get instant access to pre-configured cloud desktops containing all of the software and data you need for the project. Everything is already set up directly in your Internet browser so you can just focus on learning. For this project, you’ll get instant access to a cloud desktop with (e.g. Python, Jupyter, and Tensorflow) pre-installed. Prerequisites: In order to be successful in this project, you should be familiar with Python, Keras, Neural Networks. Notes: - You will be able to access the cloud desktop 5 times. However, you will be able to access instructions videos as many times as you want. - This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions....

人気のレビュー

AG

2020年6月16日

I like the way we got involved into practice by setting goals which are a bit challenging yet we want to achieve successfully.

NB

2020年8月2日

worth enrolling!! checkout in detail about this project even after completion

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Siamese Network with Triplet Loss in Keras: 1 - 19 / 19 レビュー

by Isra P

2020年4月12日

by Joerg A

2020年5月27日

by Abhishek P G

2020年6月17日

by Luis A G L

2020年9月22日

by Nittala V B

2020年8月3日

by Fabian L

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by Angshuman S

2020年6月15日

by XAVIER S M

2020年6月2日

by Doss D

2020年6月14日

by Sourav D

2020年5月31日

by Santiago G

2020年11月5日

by sarithanakkala

2020年6月24日

by Qasim K

2021年12月4日

by Siddhesh S

2020年4月20日

by Sri C

2020年12月4日

by Simon S R

2020年9月4日

by Jorge G

2021年2月25日

by Yannik U

2022年3月16日

by Molin D

2020年8月8日