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Machine learning is a process through which computers learn to do things by generalizing from observations rather than following pre-specified rules.

Open learner models give learners access to a computer’s representation of them to support learning. Learners may also be given the opportunity to negotiate that representation with the software.

Inspired by the working of the brain, neural networks are computer programs made up of simple, highly connected elements that learn the underlying relationships within data through considering examples.

Mia Learning uses a type called deep convolutional neural networks. These networks use many layers of filters that identify increasingly abstract features within data, culminating in identification of the feature of interest, such as a particular named entity within a text. The network learns the optimal values for the filters and the weights of connections between them through training.

Natural language understanding is a form of artificial intelligence that seeks to enable computers to understand the structure and meaning of text written or spoken in a human language.

Named entity recognition is the process of identifying references within a text to pre-defined categories. It is a form of natural language understanding.