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Volver a Siamese Network with Triplet Loss in Keras

Opiniones y comentarios de aprendices correspondientes a Siamese Network with Triplet Loss in Keras por parte de Coursera Project Network

4.7
estrellas
102 calificaciones
17 reseña

Acerca del Curso

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....

Principales reseñas

AG
16 de jun. de 2020

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

NB
2 de ago. de 2020

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

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1 - 18 de 18 revisiones para Siamese Network with Triplet Loss in Keras

por Isra P

12 de abr. de 2020

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

por Joerg A

27 de may. de 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 !)

por Abhishek P G

17 de jun. de 2020

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

por Luis A G L

22 de sep. de 2020

It is useful as you learn exactly what you expect to learn, with just the right amount of theory.

por Nittala V B

3 de ago. de 2020

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

por Fabian L

14 de jun. de 2020

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

por Angshuman S

15 de jun. de 2020

Nice crisp and knowledgeable course

por XAVIER S M

2 de jun. de 2020

Very Helpful !

por Doss D

14 de jun. de 2020

Thank you

por Sourav D

31 de may. de 2020

Excellent

por Santiago G

5 de nov. de 2020

Thanks!

por sarithanakkala

24 de jun. de 2020

Good

por Qasim K

4 de dic. de 2021

Great introductory course. Would have given 5 if the dataset was a little more complex and a real-world use case was covered.

por Siddhesh S

20 de abr. de 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.

por Sri C

4 de dic. de 2020

Not at all enough to start with a face recognition kind of use cases. The intro was cool with the explanation of using siamese network for FR kind of use-cases. But lost its cool when explaining it with mnist dataset. There's already a lot of stuff available in market and on net regarding mnist. It would have been nice if the instructor had explained some other use case too, for better understanding. The network was too small to understand the complexities of siamese network.

por Simon S R

4 de sep. de 2020

One of the few courses with an instructor actually present in the forum. However, this project needs both, more hands-on exercise and a deeper dive into the theory.

por Jorge G

25 de feb. de 2021

I do not recommend taking this type of course, take one and pass it, however after a few days I have tried to review the material, and my surprise is that it asks me to pay again to be able to review the material. Of course coursera gives me a small discount for having already paid it previously.

por Molin D

8 de ago. de 2020

Good, but not recommend.