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Über den Kurs

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-Bewertungen

AF

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. :-)

AS

Jun 20, 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 - 10 von 10 Bewertungen für Image Compression and Generation using Variational Autoencoders in Python

von 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. :-)

von 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

von Debadri B

May 29, 2020

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

von JONNALA S R

May 07, 2020

Good Initiation..

von Gaikwad N

Jul 23, 2020

Excellent

von Doss D

Jul 02, 2020

Thank you

von aithagoni m

Jul 13, 2020

good

von p s

Jun 26, 2020

Nice

von sarithanakkala

Jun 25, 2020

Good

von tale p

Jun 17, 2020

good