An examination of whether a more sophisticated learner will always result in better performance in a text-based classifier, and the trade-off between accuracy and training time.
Investigations that provide insights on how to choose an N-gram feature that maximizes performance of a classifier.
In this code story, we explore how the topology of a deep neural network can affect the performance of a text-based classifier.
Utilising deep learning to detect emotions from short, informal English text.
In this code story, we consider how data preparation can impact the performance of a classifier, and how that may lead to a refinement of problem statement, i.e. the important question we are asking.
In this code story, we create an NPM module that enables Node developers to update the Windows Registry and create file associations, as well as show how to use native Windows APIs from Node.js.
Implementing spatial capabilities by mapping entities to unique grid numbers in large-scale cloud-based table storage, like Microsoft Azure Table Storage.
