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Music Generation - Google Magenta Best Demo NIPS 2016 LSTM RNN - Deep Learning: Zero to One

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Manage episode 230562701 series 1397651
Content provided by Sam Putnam. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Sam Putnam or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://staging.podcastplayer.com/legal.
I talk through generating 10 melodies, two of which I play at the conclusion using a model trained on thousands of midi examples contained in a .mag Magenta file bundle. I used the Biaxial RNN (https://github.com/hexahedria/biaxial-rnn-music-composition) by a student named Daniel Johnson and the Basic RNN (https://github.com/tensorflow/magenta/tree/master/magenta/models/melody_rnn#basic) by Google's Magenta group within TensorFlow and learned that priming a melody with a single note can set the key for each generated melody, and, Anaconda's single 'source activate' line replaces the need for virtualenv and installs all of the necessary dependencies to make this environment easily reproducible. 2 - 3 more details are posted at: https://medium.com/@SamPutnam/deep-learning-zero-to-one-music-generation-46c9a7d82c02
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6 episodes

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Manage episode 230562701 series 1397651
Content provided by Sam Putnam. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Sam Putnam or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://staging.podcastplayer.com/legal.
I talk through generating 10 melodies, two of which I play at the conclusion using a model trained on thousands of midi examples contained in a .mag Magenta file bundle. I used the Biaxial RNN (https://github.com/hexahedria/biaxial-rnn-music-composition) by a student named Daniel Johnson and the Basic RNN (https://github.com/tensorflow/magenta/tree/master/magenta/models/melody_rnn#basic) by Google's Magenta group within TensorFlow and learned that priming a melody with a single note can set the key for each generated melody, and, Anaconda's single 'source activate' line replaces the need for virtualenv and installs all of the necessary dependencies to make this environment easily reproducible. 2 - 3 more details are posted at: https://medium.com/@SamPutnam/deep-learning-zero-to-one-music-generation-46c9a7d82c02
  continue reading

6 episodes

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