Chevron Left
Voltar para Image Compression and Generation using Variational Autoencoders in Python

Comentários e feedback de alunos de Image Compression and Generation using Variational Autoencoders in Python da instituição Coursera Project Network

4.7
estrelas
71 classificações

Sobre o 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....

Melhores avaliações

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

Filtrar por:

1 — 13 de 13 Avaliações para o Image Compression and Generation using Variational Autoencoders in Python

por Aida F

29 de jul de 2020

por Thomas J V

18 de set de 2020

por ANKIT B S

20 de jun de 2020

por Debadri B

29 de mai de 2020

por Fernando C

28 de set de 2020

por JONNALA S R

7 de mai de 2020

por Gaikwad N

23 de jul de 2020

por Doss D

2 de jul de 2020

por aithagoni m

13 de jul de 2020

por p s

25 de jun de 2020

por sarithanakkala

25 de jun de 2020

por tale p

17 de jun de 2020

por Simon S R

29 de ago de 2020