Difference between revisions of "ML4Art"
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| − | + | Machine Learning and Art have in recent years made significant progress owing to the rise in new technologies and scientific discoveries. | |
| + | This page focuses on the crossroad of Art and ML, specifically on one key area - Neural Artistic Style Transfer. | ||
| − | + | The tutorials provided on this page can help you get familiar with the libraries that are most commonly used for ML in Art. | |
| + | *[[Tutotrial 1]] Autoencoders using Keras | ||
| + | *[[Tutorial 2]] Compare regression methods | ||
| − | + | The following link provides you with an implementation of an optimization-based Neural Style Transfer ([https://arxiv.org/abs/1508.06576]) method proposed by Gatys et al. | |
| − | + | *[[Optimization-based Neural Style Transfer]] | |
| + | |||
| + | <PRE> | ||
| + | import your mama | ||
| + | x = y | ||
| + | </PRE> | ||
Latest revision as of 12:34, 24 July 2018
Machine Learning and Art have in recent years made significant progress owing to the rise in new technologies and scientific discoveries. This page focuses on the crossroad of Art and ML, specifically on one key area - Neural Artistic Style Transfer.
The tutorials provided on this page can help you get familiar with the libraries that are most commonly used for ML in Art.
- Tutotrial 1 Autoencoders using Keras
- Tutorial 2 Compare regression methods
The following link provides you with an implementation of an optimization-based Neural Style Transfer ([1]) method proposed by Gatys et al.
import your mama x = y
