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Deep Learning: Zero to One  

Deep Learning: Zero to One

Deep Learning for Enterprise

Author: Sam Putnam

Find me on Github/Twitter/Kaggle @SamDeepLearning. Find me on LinkedIn @SamPutnam. This Podcast is supported by Enterprise Deep Learning Cambridge/Boston New York City Hanover, NH http://www.EnterpriseDeepLearning.com. Contact: Sam@EDeepLearning.com, 802-299-1240, P.O. Box 863, Hanover, NH, USA, 03755. We move deep learning to production. I teach the worldwide Deploying Deep Learning Masterclass at http://www.DeepLearningConf.com in NYC regularly and am a Deep Learning Consultant serving Boston and New York City. If you like Talking Machines, harvardnlp, CS231n, the Media Lab, CSAIL, karpathy.github.io, FAIR, Google Brain, Deeplearning4j, TensorFlow, Amazon Web Services, or Google Cloud Platform, you will like the podcast. Try it. Tweet at @SamDeepLearning if you have questions & to correct me!
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Language: en-us

Genres: Technology

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Art Generation - Facebook AI Research, Google DeepDream, and Ruder's Style Transfer for Video - Deep Learning: Zero to One
Tuesday, 18 April, 2017

Justin Johnson, now at Facebook, wrote the original Torch implementation of the Gatys 2015 paper, which combines the content of one image and the style of another image using convolutional neural networks. Manuel Ruder’s newer 2016 paper transfers the style of one image to a whole video sequence, and it uses a computer vision technique called optical flow to generate consistent and stable stylized video sequences. Ruder’s implementation was used, by me, to generate a stylized butterfly video, located at https://medium.com/@SamPutnam/deep-learning-zero-to-one-art-generation-b532dd0aa390

 

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