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Machine Learning for Artists / ITP-NYU – Spring 2016

ml_cubist_expressionist_impressionist

The following is a documentation of a new course ran by Gene Kogan on Machine Learning for Artists at ITP-NYU in spring 2016.

The full video lectures and class notes can be found here and include general introduction to neural networks, applications, wekinator, convolutional neural networks, convnet applications, recurrent neural networks and game AI + deep reinforcement learning. Over 12 hours of video with examples.

If you are at all interested in Machine Learning (we surely are), Gene has created an invaluable resource for all of us here. Thank you!

More → ITP-NYU – Spring 2016 | Gene Kogan

↑ image above – Style transfer [2015] by Gene Kogan – a technique of recomposing images in the style of other images using convolutional neural networks.