DSS-2019-07: ANANTH CHAKRAVARTHY and JON PATRICK

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Commonwealth Bank of Australia

South Building 1 Harbour Street · Sydney

How to find us

Please go to Commonwealth Bank Place (South Building) in Darling Harbour.

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Details

Data Science Sydney presents our July 2019 event:

ANANTH CHAKRAVARTHY: "Rapid feature harvesting using DFS"

JON PATRICK:"Clinical Language Engineering: Dos and Don’ts of Industrial Statistical NLP"

200 seats available, first come, first served for members on the RSVP-yes list. Please ensure that you keep your RSVP up to date. If you cannot make it, please make your spot available for others as soon as possible.

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To comply with CBA Security we need your FIRST and LAST NAME before the event. If these are not your profile name, please enter them when you register. Members who do not provide first and last name will be removed from the guest list and will not be able to attend.

Registration opens at 5:30pm and close at 6:15pm, sharp. Food and beverages between 6pm and 6:15pm. Late comers cannot be admitted.

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ANANTH CHAKRAVARTHY: "Rapid feature harvesting using DFS"

The talk: As machine learning adoption permeates across many business models, so is the need to deliver models at a much faster rate. Feature engineering arguably is one of the core foundations of model development cycle. Automating feature engineering would immensely shorten the time to market classical machine learning models.
Deep Feature Synthesis (DFS) is an algorithm that is implemented in the FeatureTools python package. DFS helps in rapid harvesting of new features by taking a stacking approach on top of a relational data model. DFS also has first class support for time dimensions as a fundamental construct. However the base algorithm itself can be enriched in multiple ways to make it truly appealing for many other use cases. This session will present a summary of DFS algorithmic constructs followed by enhancements that can be done on featuretools library to enable it for many other use cases

The author: Ananth is a senior application architect in the Decisioning and Advanced Analytics engineering team for Commonwealth Bank of Australia working for the next generation architectures for CBA fraud platform and Advanced Analytics Omnia platform at CBA. He holds a PhD degree in the domain of computer science security. He holds 3 patents granted by USPTO. Prior to to CBA, he was an architect at Threatmetrix. He is a committer for Apache Apex and has presented at a number of conferences including the YOW Data and Dataworks summit in Australia.
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JON PATRICK: "Clinical Language Engineering: Dos and Don'ts of Industrial Statistical NLP"

The talk: research methods for building machine learning models have a number fo standard practices that everyone normally abides by. But is that the way we should operate when we have to deliver solutions to clients that have to become part of their productions process. This topic will discussed with examples drawn from processing clinical documents (e.g. pathology or radiology reports) for document classification, Clinical Entity Recognition and medical taxonomic coding.

The author: Jon Patrick held the Chair of Information Systems at the UniversIty of Sydney from 1998 to 2004 and then moved to the Chair of Language Technology. In 2005 he won the Australia’s national
Eureka Science prize for his work in natural language processing. He has conducted extensive research on the use of language technology in Intensive Care, Pathology and Radiology departments, and in information systems research in emergency medicine and oncology. In 2012 he left the University of Sydney to pursue his interests in R&D in Health IT and NLP and is the CEO for the companies Health Language Analytics (HLA) and its subsidiary Health Language Analytics Global and Innovative Clinical Information Management Systems (iCIMS).
Recently the work of the two companies at the Sydney Adventist Hospital has been highlighted in Pulse IT at https://www.pulseitmagazine.com.au/australian-ehealth/4980-the-san-rolls-out-icims-cancer-information-management-system-for-mdts.