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Learner Reviews & Feedback for Image Compression and Generation using Variational Autoencoders in Python by Coursera Project Network

4.7
stars
76 ratings

About the Course

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....

Top reviews

AF

Jul 28, 2020

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

AS

Jun 19, 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 of 13 Reviews for Image Compression and Generation using Variational Autoencoders in Python

By Aida F

•

Jul 29, 2020

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

By Thomas J V

•

Sep 18, 2020

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

By ANKIT B S

•

Jun 20, 2020

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

By Debadri B

•

May 29, 2020

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

By Fernando C

•

Sep 28, 2020

A great knowledge of how to use VAEs in PyTorch.

By JONNALA S R

•

May 7, 2020

Good Initiation..

By Gaikwad N

•

Jul 23, 2020

Excellent

By Doss D

•

Jul 2, 2020

Thank you

By aithagoni m

•

Jul 13, 2020

good

By p s

•

Jun 25, 2020

Nice

By sarithanakkala

•

Jun 25, 2020

Good

By tale p

•

Jun 17, 2020

good

By Simon S R

•

Aug 29, 2020

Cannot recommend it.