Event Details

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Accessible ML: combining Open Source and Open Data

If you think that only big tech companies or PhD scientists can use ML & AI, I'd like to show you that an individual open-source enthusiast can build and train a model on comodity hardware using Open Data - and then scale that up on a public cloud.

If you're a gamer and a python developer, you might already have all the tools you need!

* fast.ai, an easy-to-learn Python ML framework
* nvidia-docker on an Ubuntu Gaming PC
* public-domain GIS imagery
* a couple terabytes of storage space and a fast internet connection

This talk grew out of the Firewise project, which I helped bootstrap last year. We aimed to use public-domain sattelite imagery to help predict and prevent forest fires. Even though the founders chose not to pursue this as a business, it's an excellent example of how easily open source and public data can be combined to benefit society.


What can I expect to learn?

- discussion of open source ethos, enabling independent development efforts, social causes.

- raising awareness of public-domain Open Data

- introduction to ML tools which are easy enough for any Python developer to adopt - no data science background needed!

Wednesday, May 1, 9:50am-10:30am (3:50pm - 4:30pm UTC)
Difficulty Level: Beginner
Microsoft, Sr Software Engineer
Aeva Black is a radically queer geek and lifelong student of the dharma, a Linux user since the mid '90s, and has been an advocate for Open Source since 2003. They pioneered the creation of the OpenStack Bare Metal Cloud project while working at HPE, and have contributed to projects such as MySQL, Ansible, and Kubernetes. Today, they are the Open Source Program Manager for the Azure... FULL PROFILE