Event Details

Please note: All times listed below are in Central Time Zone

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
Open Source Program Manager
Aeva Black is an open source hacker and a veteran of the first dot-com bust. Today, they work in Azure’s Office of the CTO and serve the open source community as the Secretary of the Board for the Open Source Initiative and as a member of the OpenSSF’s Technical Advisory Council. When not working or speaking at conferences, Aeva enjoys exploring the Pacific Northwest on a motorcycle. FULL PROFILE