Clojure for Data Science: from a Prototype in Python to Clojure in Production
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HealthUnlocked is a social network centred around health issues, where people find information about chronic conditions. Our users share 4.5 pieces of health content every minute, which we classify into 700 different categories within milliseconds using machine learning.
The data science team at HealthUnlocked is used to using mature Python libraries to process text and implement machine learning algorithms. During this talk, you will explore a journey to translate a Python model prototype into Clojure production code.
You will learn how the HU team implemented our natural language processing pipeline, including tokenisation and vectorisation, as well as the core Naive Bayes algorithm, from first principles.
YOU MAY ALSO LIKE:
- Now you're Speaking my Language! : Building, Maintaining and Using a Patient-Friendly Medical Ontology (SkillsCast recorded in December 2018)
- Real-time Systems with Spark Streaming and Kafka (in London on 30th September - 1st October 2019)
- µCon London 2020 - The Conference on Microservices, DDD & Software Architecture (in London on 27th - 29th May 2020)
- Keynote Evening by Brian Ketelsen! (in London on 17th October 2019)
- Leonardo De Marchi's Deep Learning Fundamentals (in London on 22nd - 23rd October 2019)
- Brian Sletten's Data Science with Python Workshop (in London on 18th - 20th November 2019)
- ProgNET London 2019 (in London on 11th - 13th September 2019)
- CloudNative London 2019 (in London on 25th - 27th September 2019)
- London Reinforcement Learning August (in London on 22nd August 2019)
- You got served: How Deliveroo improved the ranking of restaurants (in London on 27th August 2019)
- Telling Human Stories With Data (SkillsCast recorded in August 2019)
- London #PowerBI user group with Will Thompson (SkillsCast recorded in August 2019)
Thanks to our sponsors
Clojure for Data Science: from a Prototype in Python to Clojure in Production
Chloe Pont
Chloe is currently part of the data science team at HealthUnlocked which aims to improve user experience on the platform and facilitate user data analysis. She has always been passionate about healthcare and psychology and she enjoys digging for new insights in medical data.
Maria Mestre
Maria is the lead data scientist at HealthUnlocked, a health social network. Her main role is to build the data pipelines and machine algorithms that power THE team's content recommender and intelligent content tagger. Before working at HealthUnlocked, she did a PhD in Cambridge in signal processing & machine learning. She then moved to work at a startup using mainly big data tools (Spark) and Python.
Please log in to watch this conference skillscast.
HealthUnlocked is a social network centred around health issues, where people find information about chronic conditions. Our users share 4.5 pieces of health content every minute, which we classify into 700 different categories within milliseconds using machine learning.
The data science team at HealthUnlocked is used to using mature Python libraries to process text and implement machine learning algorithms. During this talk, you will explore a journey to translate a Python model prototype into Clojure production code.
You will learn how the HU team implemented our natural language processing pipeline, including tokenisation and vectorisation, as well as the core Naive Bayes algorithm, from first principles.
YOU MAY ALSO LIKE:
- Now you're Speaking my Language! : Building, Maintaining and Using a Patient-Friendly Medical Ontology (SkillsCast recorded in December 2018)
- Real-time Systems with Spark Streaming and Kafka (in London on 30th September - 1st October 2019)
- µCon London 2020 - The Conference on Microservices, DDD & Software Architecture (in London on 27th - 29th May 2020)
- Keynote Evening by Brian Ketelsen! (in London on 17th October 2019)
- Leonardo De Marchi's Deep Learning Fundamentals (in London on 22nd - 23rd October 2019)
- Brian Sletten's Data Science with Python Workshop (in London on 18th - 20th November 2019)
- ProgNET London 2019 (in London on 11th - 13th September 2019)
- CloudNative London 2019 (in London on 25th - 27th September 2019)
- London Reinforcement Learning August (in London on 22nd August 2019)
- You got served: How Deliveroo improved the ranking of restaurants (in London on 27th August 2019)
- Telling Human Stories With Data (SkillsCast recorded in August 2019)
- London #PowerBI user group with Will Thompson (SkillsCast recorded in August 2019)
Thanks to our sponsors
Clojure for Data Science: from a Prototype in Python to Clojure in Production
Chloe Pont
Chloe is currently part of the data science team at HealthUnlocked which aims to improve user experience on the platform and facilitate user data analysis. She has always been passionate about healthcare and psychology and she enjoys digging for new insights in medical data.
Maria Mestre
Maria is the lead data scientist at HealthUnlocked, a health social network. Her main role is to build the data pipelines and machine algorithms that power THE team's content recommender and intelligent content tagger. Before working at HealthUnlocked, she did a PhD in Cambridge in signal processing & machine learning. She then moved to work at a startup using mainly big data tools (Spark) and Python.