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Data comes in many forms, all of it messy. Whether we’re talking about missing data, unstructured data, or data that lacks regular structure, you need methods to cleanse data before you can process it to improve its quality.
In this episode, guest Sean Gupta sits down with TDS to discuss data models, risk assessment, and machine learning role in the healthcare industry. Sean also discussed why machine learning predictions based on criminal history perform better than models based on DASH features.
Sean Gupta
https://www.linkedin.com/in/arijitseangupta/
The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.
https://datastandard.io
https://www.linkedin.com/company/the-data-standard
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Data comes in many forms, all of it messy. Whether we’re talking about missing data, unstructured data, or data that lacks regular structure, you need methods to cleanse data before you can process it to improve its quality.
In this episode, guest Sean Gupta sits down with TDS to discuss data models, risk assessment, and machine learning role in the healthcare industry. Sean also discussed why machine learning predictions based on criminal history perform better than models based on DASH features.
Sean Gupta
https://www.linkedin.com/in/arijitseangupta/
The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.
https://datastandard.io
https://www.linkedin.com/company/the-data-standard
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q