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Avis et commentaires pour d'étudiants pour Siamese Network with Triplet Loss in Keras par Coursera Project Network

4.8
étoiles
62 évaluations
10 avis

À propos du cours

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....

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1 - 11 sur 11 Avis pour Siamese Network with Triplet Loss in Keras

par Joerg A

May 27, 2020

Very well instructed, I learned both a new technology and something for good python programming habits. Explanations come to the point and still are deep. Test are not stupid simple questions, but still easy to answer. And I got the impression the instructor even knows about the pain with Rhyme (and seems to do something about it !)

par Abhishek P G

Jun 17, 2020

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

par Nittala V B

Aug 03, 2020

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

par Fabian L

Jun 14, 2020

it's so great for two hours, is just a preview, but is good

par Angshuman S

Jun 15, 2020

Nice crisp and knowledgeable course

par XAVIER S M

Jun 02, 2020

Very Helpful !

par Doss D

Jun 14, 2020

Thank you

par Sourav D

Jun 01, 2020

Excellent

par sarithanakkala

Jun 24, 2020

Good

par Siddhesh S

Apr 20, 2020

This course has nice content, but the usage is difficult. Ever after having fast internet, the videos and the environment were so slow, making it almost impossible to be used.

par Isra P

Apr 13, 2020

Incomplete course, the prediction is very important not only training!