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SkillsCast

Data Science in Languages I Don’t Understand

3rd December 2018 in London at CodeNode

There are 26 other SkillsCasts available from Clojure eXchange 2018

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Wefarm, the world’s largest farmer-to-farmer digital network, lets small-scale farmers connect with one another to solve problems, share ideas and spread innovation — all for free. With Wefarm, farmers can share and access crucial crop and livestock information about how to improve their yield or battle a disease without leaving their farm, spending any money, or having any access to the internet.

At Wefarm, Clojure and Natural Language Processing (NLP) has been used to design a service that works over SMS – in regional African languages not supported by any standard library – and that is robust to plenty of variation in spelling and punctuation. The flexibility of Clojure has enabled the build from a legacy system that only understands simple commands, to a conversational interface capable of understanding the intent and content of messages, and responding appropriately.

During this talk, you will discover models (Bayesian and elsewise), approaches (intent-matching with patterns written in a subset of Clojure), and tools (mini-REPLs) that have been used along the way.

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Thanks to our sponsors

Data Science in Languages I Don’t Understand

Rob Stanley

Rob is Head of Data at Wefarm, using Clojure, R, and Data Science/Machine Learning to help farmers get improved access to the vital information they need.

SkillsCast

Please log in to watch this conference skillscast.

Https s3.amazonaws.com prod.tracker2 resource 41088130 skillsmatter conference skillscast o9nohu

Wefarm, the world’s largest farmer-to-farmer digital network, lets small-scale farmers connect with one another to solve problems, share ideas and spread innovation — all for free. With Wefarm, farmers can share and access crucial crop and livestock information about how to improve their yield or battle a disease without leaving their farm, spending any money, or having any access to the internet.

At Wefarm, Clojure and Natural Language Processing (NLP) has been used to design a service that works over SMS – in regional African languages not supported by any standard library – and that is robust to plenty of variation in spelling and punctuation. The flexibility of Clojure has enabled the build from a legacy system that only understands simple commands, to a conversational interface capable of understanding the intent and content of messages, and responding appropriately.

During this talk, you will discover models (Bayesian and elsewise), approaches (intent-matching with patterns written in a subset of Clojure), and tools (mini-REPLs) that have been used along the way.

YOU MAY ALSO LIKE:

Thanks to our sponsors

About the Speaker

Data Science in Languages I Don’t Understand

Rob Stanley

Rob is Head of Data at Wefarm, using Clojure, R, and Data Science/Machine Learning to help farmers get improved access to the vital information they need.

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