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Published on May 6, 2017
A Keynote talk filmed at PyData London 2017
Description A talk about the flourishing intersection between machine learning and art, a survey of recent works emerging from it, and a primer on how to get started with it for seasoned developers and newcomers alike.
Abstract Over the past several years, two trends in machine learning have converged to pique the curiosity of artists working with code: the proliferation of powerful open source deep learning frameworks like TensorFlow and Torch, and the emergence of data-intensive generative models for hallucinating images, sounds, and text as though they came from the oeuvre of Shakespeare, Picasso, or just a gigantic database of digitized cats. This talk will review these developments and offer a set of interdisciplinary tools and learning resources for artists and data scientists alike, if ever there was a difference to begin with.
PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R.
We aim to be an accessible, community-driven conference, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.