Speaker - Steven Cooper

12 September 2016 – Posted by Gareth Evans

Machine learning your way to smarter API error responses

Machine learning is quickly becoming a common place method to handle the grey area of user requests and interaction. From messaging chat apps to even the most basic of online ordering its quickly become a way to gauge user input and attempt to not only respond with a best match response but also add the user interaction to the base pair program. In this talk we are going to look at ways that we can use machine learning to a new level and attempt to handle malformed API requests in a new way and attempt to decipher unmatchable requests in a way that will try and not only respond with a best fit response but capture the user errors for future responses.


As a Senior Evangelist at Xero Steven Cooper is responsible for working with the strong global developer community, to develop and nurture the healthy start-up culture that continues to flourish across the region.

Among his activities in the international community Steven has helped run the acclaimed BattleHack series for PayPal/Braintree all over the world. An international speaker and mentor that has been a part of events throughout the world he loves to share knowledge and help support and grow developer communities.

Over the last 20 years, Steven has worked as a senior developer/tech lead for a host of start-ups and as a developer analyst for more than 10 years with Sensis. He has configured and spec’d mass production technology hardware for the likes of Samsung, Virgin, Coca-Cola, Pepsi, Visa, St. George and Westpac.

Steven hopes to align businesses with the most appropriate solutions – products that deliver efficiency, flexibility and enable scalability.

Talk Slides

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