| Machine Learning: GANS Josh Murr |
19.01.21 / 21.01.21
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Generative Adversarial Networks (GAN)
have become the leading machine learning model
architecture for those looking to produce novel high-quality images. The aim
of the first part of this workshop is give a high-level understanding of what
a GAN is and to find out why they are so good at generating images. You will also be
shown how to build a dataset from a video online and use that to train a model
as homework using
Google Colab.
In the second session we will upload these models to an
online platform where you will be able to interact with the model in real time to
explore the limits and capabilities of the model created. Finally, information
and advice will be given as to where to learn more, what useful tools are
out there and how
to take things further.
Josh Murr will be leading this workshop.
We are very excited to be collaborating with the UAL Creative Computing Institute to offer this opportunity to accelerate your work with GANS.
Creativity plus computation with CSM Digital Innovation Season + UAL Creative Computing Institute.
Josh Murr
Josh Murr has an interest in making rich interactive experiences online. Recent research has been in exploring the possibilities of generative machine learning on the web for image/video making, educational purposes and bringing seemingly complex systems on to everyday computers.
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We are very excited to be collaborating with the UAL Creative Computing Institute to offer this opportunity to accelerate your work with GANS.
Creativity plus computation with CSM Digital Innovation Season + UAL Creative Computing Institute.
Josh Murr
Josh Murr has an interest in making rich interactive experiences online. Recent research has been in exploring the possibilities of generative machine learning on the web for image/video making, educational purposes and bringing seemingly complex systems on to everyday computers.
#
2x 2h workshops
Tuesday 19th January - 6pm-8pm GMT
Thursday 21st January - 6pm-8pm GMT
Software:
Familiarity with Python would be beneficial but not essential.
Tuesday 19th January - 6pm-8pm GMT
Thursday 21st January - 6pm-8pm GMT
Software:
Familiarity with Python would be beneficial but not essential.
