We've all wondered how to use Machine Learning with Go, but what about turning the tables for once? What can Machine Learning do *for* Go? During this presentation, we will discover how different Machine Learning models can help us write better go by predicting from our next character to our next bug!
Francesc’s talk will cover the basics of what Machine Learning techniques can be applied to source code, specifically:
- [embeddings over identifiers] (https://bit.ly/2HEcQhg)
- structural embeddings over source code, answering the question of how similar two fragments of code are,
- recurrent neural networks for code completion,
- future direction of the research.
While the topic is advanced, the level of mathematics required for this talk will be kept to a minimum. Rather than getting stuck in the details, we'll discuss the advantages and limitations of these techniques, and their possible implications to our developer lives.