Creative Applications of Deep Learning with TensorFlow


Deep learning has emerged at the forefront of nearly every major computational breakthrough in the last four years. It’s no wonder that it’s already in many of the products that we use today. From Netflix or Amazon personalized recommendations, to the filters that block our spam, or to the ways that we interact with personal assistants like Apple Siri or Microsoft Cortana. And sure, deep learning algorithms are capable of some amazing things, but it’s not just science applications that are benefiting from this research. Artists too are starting to explore how deep learning can be used in their own practice. I’m Parag Mital artist, researcher, and director of machine intelligence at Kadenze. In this course, we’re going straight to the state of the art. We’re going to learn it all. We’ll see how to make an algorithm paint an image or hallucinate objects in a photograph. We’ll see how to train a computer to recognize objects in an image and use this knowledge to drive new and interesting behaviors, from understanding the similarities and differences in large data sets to using them to self-organize, to understanding how to infinitely generate entirely new content, or match the aesthetics or contents of other images. We’ll even see how to teach your computer to read and synthesize new phrases. But we won’t just be using other people’s code to do all of this We’re going to develop everything ourselves using TensorFlow, and I’m going to show you how to do it. This course isn’t just for artists, nor is it just for programmers, it’s for people who want to learn more about how to apply deep learning with the hands-on approach, straight into the iPython console, and learn what it all means through creative thinking and interaction. Join me as we learn all about creative applications of deep learning with TensorFlow.

4 Comments

  1. Gopher

    July 19, 2016 at 11:57 am

    annoying distracting background music

  2. Cayman Roe

    February 19, 2017 at 9:31 pm

    Background music if far too loud, but other than that interesting video. Thanks for making this.

  3. scipilot

    August 27, 2017 at 3:23 am

    I could barely hear a word he said.

  4. rchavezj

    June 29, 2019 at 2:14 am

    This class is really kol. I hope to see a pytorch version

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