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.
- 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!