Droidcon Boston '19: Code + ML: Will Automation Take Our Jobs?
MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 39M | 213 MB
Genre: eLearning | Language: English
This talk will provide an overview of fundamental concepts of machine learning, delve into how it can be used to analyze and improve code, provide pointers to available commercial and open source tools, and discuss what's been achieved so far.
Did you know "neural-network based classification" is really just a fancy way to squish a bunch of data until all the things that look alike are right next to each other? Machine learning is permeating every facet of our lives, from learning our preferences to self-driving cars, but what happens when you apply neural networks to code quality...how do you even view code as data? The key ideas are pretty easy to summarize and fun to play with. This talk will provide an overview of fundamental concepts of machine learning, and then delve into how it can be used to analyze and improve code, provide pointers to available commercial and open source tools and discuss what's been achieved so far (coding in English, context-aware code completion, automated Stack Overflow). The talk will close with speculation on where the field is going, and how machine learning won't take our jobs, but hopefully will take some of the work we don't like doing.
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