ML has revolutionized many fields from cancer detection to self-driving cars, and let’s not forget about connected toilets that allow Alexa to flush at your command. Researchers have been working on applying ML to source code to predict bugs, find patterns in code, and much more; source{d} is building products to apply this research to improve day-to-day developer tasks.
Francesc Campoy explores the most useful techniques and relevant research, focusing on use cases where ML can help developers be more efficient.
Francesc Campoy is the VP of Product at Dgraph: the most advanced distributed graph database.
Before that, he was VP of Product and Developer Relations at source{d}, the company enabling Machine Learning for large scale code analysis and building the platform for the future of developer tooling. Previously, he worked at Google as Senior Developer Advocate for Google Cloud Platform and the Go team.
He’s passionate about programming and programmers, especially Go and gophers. As part of his effort to help those learning, he’s given many talks and workshops at conferences like Google I/O, Gophercon(s), GOTO, or OSCON.
When he’s not on stage he’s probably coding, writing blog posts, or working on his justforfunc YouTube series where he hacks while cracking bad jokes.
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