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Deep Learning: Zero to One - Podcast

Deep Learning: Zero to One

 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: [email protected], 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!

Learning Technology Deep
Update frequency
every 22 days
Average duration
27 minutes
Episodes
3
Years Active
2017
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Art Generation - Facebook AI Research, Google DeepDream, and Ruder's Style Transfer for Video - Deep Learning: Zero to One

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

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 net…
00:07:49  |   Tue 18 Apr 2017
Music Generation - Google Magenta Best Demo NIPS 2016 LSTM RNN - Deep Learning: Zero to One

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

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…
01:09:30  |   Mon 13 Mar 2017
Image Generation - Google DeepMind paper with TensorFlow - Deep Learning: Zero to One

Image Generation - Google DeepMind paper with TensorFlow - Deep Learning: Zero to One

I talk through generating an image of IRS tax return characters using a model trained on the IRS tax return dataset - NMIST. The authors trained for 70 hours on 32 GPUs. I used unconditioned image ge…
00:05:01  |   Sat 04 Mar 2017
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