How to Generate Art - Intro to Deep Learning #8

We're going to learn how to use deep learning to convert an image into the style of an artist that we choose. We'll go over the history of computer generated art, then dive into the details of how this process works and why deep learning does it so well.

Coding challenge for this video:
https://github.com/llSourcell/How-to-Generate-Art-Demo

Itai's winning code:
https://github.com/etai83/lstm_stock_prediction

Andreas' runner up code:
https://github.com/AndysDeepAbstractions/How-to-Predict-Stock-Prices-Easily-Demo/blob/master/stockdemo.ipynb

More learning resources:
https://harishnarayanan.org/writing/artistic-style-transfer/
https://ml4a.github.io/ml4a/style_transfer/
http://genekogan.com/works/style-transfer/
https://arxiv.org/abs/1508.06576
https://jvns.ca/blog/2017/02/12/neural-style/

Style transfer apps:
http://www.pikazoapp.com/
http://deepart.io/
https://artisto.my.com/
https://prisma-ai.com/

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Song at the beginning is called Everyday by Carly Comando
jurassic park inception visualization is from http://www.pyimagesearch.com/2015/07/06/bat-country-an-extendible-lightweight-python-package-for-deep-dreaming-with-caffe-and-convolutional-neural-networks/
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Видео How to Generate Art - Intro to Deep Learning #8 канала Siraj Raval