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Volver a Image Compression and Generation using Variational Autoencoders in Python

Opiniones y comentarios de aprendices correspondientes a Image Compression and Generation using Variational Autoencoders in Python por parte de Coursera Project Network

4.7
estrellas
68 calificaciones
13 reseña

Acerca del Curso

In this 1-hour long project, you will be introduced to the Variational Autoencoder. We will discuss some basic theory behind this model, and move on to creating a machine learning project based on this architecture. Our data comprises 60.000 characters from a dataset of fonts. We will train a variational autoencoder that will be capable of compressing this character font data from 2500 dimensions down to 32 dimensions. This same model will be able to then reconstruct its original input with high fidelity. The true advantage of the variational autoencoder is its ability to create new outputs that come from distributions that closely follow its training data: we can output characters in brand new fonts. Note: 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

AF
28 de jul. de 2020

It is highly recommended to those who has a basic knowledge in ML and like to start using VAEs in pytorch framework. :-)

AS
19 de jun. de 2020

It was really helpful. I am new to PyTorch but it gave a good level of understanding overall. thank you

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1 - 13 de 13 revisiones para Image Compression and Generation using Variational Autoencoders in Python

por Aida F

29 de jul. de 2020

It is highly recommended to those who has a basic knowledge in ML and like to start using VAEs in pytorch framework. :-)

por ANKIT B S

20 de jun. de 2020

It was really helpful. I am new to PyTorch but it gave a good level of understanding overall. thank you

por Debadri B

29 de may. de 2020

Good project. Add some more clarity to it , especially to the mathematical background.

por Fernando C

28 de sep. de 2020

A great knowledge of how to use VAEs in PyTorch.

por JONNALA S R

7 de may. de 2020

Good Initiation..

por Gaikwad N

23 de jul. de 2020

Excellent

por Doss D

2 de jul. de 2020

Thank you

por aithagoni m

13 de jul. de 2020

good

por p s

25 de jun. de 2020

Nice

por sarithanakkala

25 de jun. de 2020

Good

por tale p

17 de jun. de 2020

good

por Thomas J V

18 de sep. de 2020

Just fine for someone who has enough idea on coding as well as some idea on VAE

por Simon S R

29 de ago. de 2020

Cannot recommend it.