This is the third in our three-part series “Lessons Learned Deploying Early Intervention Systems.” The first part (you can check it here) discussed the importance of data science deployments, while the second blog post in this series discussed the technical challenges related to the implementation. This final part is about the other (and typically more [...]
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This is the second in our three-part series “Lessons Learned Deploying Early Intervention Systems.” The first part (you can find it here) discussed the importance of data science deployments. For the past two years, we have worked with multiple police departments to build and deploy the first data-driven Early Intervention System (EIS) for police [...]
From the company’s creation, Netflix has relied on the scalability and accuracy of machine learning to deliver content and turn profits. One way Netflix uses machine learning is to recommend movies to its users. A model that provides accurate and tailored recommendations at scale is valuable because it increases the value of Netflix subscriptions at [...]
Combining datasets and performing large aggregate analyses are powerful new ways to improve service across large populations. Critically important in this task is the deduplication of identities across multiple data sets that were rarely designed to work together. Inconsistent data entry, typographical errors, and real world identity changes pose significant challenges to this process. To [...]