Logistic Regression is a widely used model in Machine Learning. It is used in binary classification, where output variable can only take binary values. Some real world examples where Logistic ...

To apply the model ... used in machine learning, including machine learning reasoning with graphs. But this approach does not explicitly leverage logical composition rules. For example, from ...

The relational database model was developed in the ... With industries increasingly adopting machine learning, it seems likely that knowledge graph technology will also evolve hand-in-hand.

The result is a machine learning framework that is easier to work with—for example, by using the relatively simple Keras API for model training ... apps. Each graph operation can be evaluated ...

With efficient algorithms, well-chosen functions and enough examples, machine learning can create powerful computational models that do things we have no idea how to program. Classification and ...

Perceptron classification is arguably the most rudimentary machine learning (ML) technique. The perceptron technique can be used for binary classification, for example predicting ... The goal of the ...

Machine learning and deep learning have been widely embraced, and even more widely misunderstood. In this article, I’ll step back and explain both machine learning and deep learning in basic ...