Image Generation - Google DeepMind Paper With TensorFlow - Deep Learning: Zero To One Deep Learning: Zero To One podcast

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Innhold levert av Sam Putnam. Alt podcastinnhold, inkludert episoder, grafikk og podcastbeskrivelser, lastes opp og leveres direkte av Sam Putnam eller deres podcastplattformpartner. Hvis du tror at noen bruker det opphavsrettsbeskyttede verket ditt uten din tillatelse, kan du følge prosessen skissert her https://no.player.fm/legal.

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

7+ y ago 5:01

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Innhold levert av Sam Putnam. Alt podcastinnhold, inkludert episoder, grafikk og podcastbeskrivelser, lastes opp og leveres direkte av Sam Putnam eller deres podcastplattformpartner. Hvis du tror at noen bruker det opphavsrettsbeskyttede verket ditt uten din tillatelse, kan du følge prosessen skissert her https://no.player.fm/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

… continue reading

6 episoder

#Tech #Deep #Nature #Language #Sam Putnam #Learn #Machining #Process

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

Deep Learning: Zero to One

125 subscribers

published 7+ y ago

Del

MP3•Episoder hjem

Innhold levert av Sam Putnam. Alt podcastinnhold, inkludert episoder, grafikk og podcastbeskrivelser, lastes opp og leveres direkte av Sam Putnam eller deres podcastplattformpartner. Hvis du tror at noen bruker det opphavsrettsbeskyttede verket ditt uten din tillatelse, kan du følge prosessen skissert her https://no.player.fm/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

… continue reading

6 episoder

#Tech #Deep #Nature #Language #Sam Putnam #Learn #Machining #Process

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