Session Overview

Thanks to the recent development of cutting-edge machine learning (ML) techniques, there is a growing number of products that are turning ML models into a long-term sustainable service with the hope that it can evolve and improve with time. In this talk, Dr. Shou-De Lin, Chief Machine Learning Scientist at Appier, will share the challenges and opportunities of deploying machine learning models as a long-term service. Typically, accuracy and efficiency have been considered as key factors for evaluating the quality of ML models, but there are many other factors to consider to ensure long-term success. This talk will cover several other important aspects including data health; modle robustness; the gap between the objective and the ultimate goal; and managing bias throughout the process.


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    Machine Learning as a Service: Challenges and Opportunities

    • Abstract & Bio

    • Machine Learning as a Service: Challenges and Opportunities


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