Learning from Imbalanced Classes - Silicon Valley Data Science
August 25th, 2016 If you’re fresh from a machine learning course, chances are most of the datasets you used were fairly easy. Among other things, when you built classifiers, the example classes were balanced, meaning there were approximately the same number of examples of each class. Instructors usually employ cleaned up datasets so as to concentrate on teaching specific algorithms or techniques w
Managing Spark and Kafka Pipelines - Silicon Valley Data Science
With Monitoring and Alerting | May 11th, 2017 Do you fully understand how your systems operate? As an engineer, there is a lot you can do to aid the person who is going to manage your application in the future. In a previous post we covered how exposing the tuning knobs of the underlying technologies to operations will go a long way to making your application successful. Your application is a un
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