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Named Entity Recognition using LSTMs with Keras

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  • Project: Named Entity Recognition using LSTMs with Keras
    • In this 1-hour long project-based course, you will use the Keras API with TensorFlow as its backend to build and train a bidirectional LSTM neural network model to recognize named entities in text data. Named entity recognition models can be used to identify mentions of people, locations, organizations, etc. Named entity recognition is not only a standalone tool for information extraction, but it also an invaluable preprocessing step for many downstream natural language processing applications like machine translation, question answering, and text summarization. The prerequisites for the project are prior Python programming experience as well as a theoretical understanding of neural networks; preferably recurrent neural networks (RNNs).