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Challenges in deploying machine learning: a survey of case studies
In recent years, machine learning has transitioned from a field of academic research interest
to a field capable of solving real-world business problems. However, the deployment of …
to a field capable of solving real-world business problems. However, the deployment of …
Urban anomaly analytics: Description, detection, and prediction
Urban anomalies may result in loss of life or property if not handled properly. Automatically
alerting anomalies in their early stage or even predicting anomalies before happening is of …
alerting anomalies in their early stage or even predicting anomalies before happening is of …
Gamut: A design probe to understand how data scientists understand machine learning models
Without good models and the right tools to interpret them, data scientists risk making
decisions based on hidden biases, spurious correlations, and false generalizations. This …
decisions based on hidden biases, spurious correlations, and false generalizations. This …
Heat map visualisation of fire incidents based on transformed sigmoid risk model
D Liu, Z Xu, Y Zhou, C Fan - Fire Safety Journal, 2019 - Elsevier
Fire is one of the most frequent disasters that threaten public safety and ecological balance.
Heat maps have been used as a common visualisation method in many scientific fields but …
Heat maps have been used as a common visualisation method in many scientific fields but …
From symbols to embeddings: A tale of two representations in computational social science
Computational Social Science (CSS), aiming at utilizing computational methods to address
social science problems, is a recent emerging and fast-develo** field. The study of CSS is …
social science problems, is a recent emerging and fast-develo** field. The study of CSS is …