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Image Generation - Google DeepMind paper with TensorFlow - Deep Learning: Zero to One
Manage episode 230562702 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 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 generation to create an image in 6 hours on my MacBook Pro CPU. I used the TensorFlow implementation of Conditional Image Generation with PixelCNN Decoders (https://arxiv.org/abs/1606.05328) by a student named Anant Gupta and learned that reasonable-looking digits can be generated with significantly fewer training steps, as soon as the training loss approaches that reached by the DeepMind authors. Each step is detailed at https://medium.com/@SamPutnam/this-is-the-1st-deep-learning-zero-to-one-newsletter-this-one-is-called-image-generation-935bcaf0f37c
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Manage episode 230562702 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 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 generation to create an image in 6 hours on my MacBook Pro CPU. I used the TensorFlow implementation of Conditional Image Generation with PixelCNN Decoders (https://arxiv.org/abs/1606.05328) by a student named Anant Gupta and learned that reasonable-looking digits can be generated with significantly fewer training steps, as soon as the training loss approaches that reached by the DeepMind authors. Each step is detailed at https://medium.com/@SamPutnam/this-is-the-1st-deep-learning-zero-to-one-newsletter-this-one-is-called-image-generation-935bcaf0f37c
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Similar to Deep Learning: Zero to One
Africa-focused technology, digital and innovation ecosystem insight and commentary.
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continue reading
Show notes are at https://stevelitchfield.com/sshow/chat.html
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continue reading
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…
continue reading
The power of Data is undeniable. And unharnessed - it’s nothing but chaos. Making data your ally. Using it to lead with confidence and clarity. Host Jess Carter is solving problems in real-time to reveal what’s possible. Helping communities and people thrive. This is Data Driven Leadership, a show brought to you by Resultant.
…
continue reading
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…
continue reading
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…
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The Talk Show With John Gruber
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On The Bike Shed, hosts Joël Quenneville and Stephanie Minn discuss development experiences and challenges at thoughtbot with Ruby, Rails, JavaScript, and whatever else is drawing their attention, admiration, or ire this week.
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continue reading
This is the audio podcast version of Troy Hunt's weekly update video published here: https://www.troyhunt.com/tag/weekly-update/
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continue reading
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