Natural Language Processing of German texts - Part 2: Using LSTM neural-networks to predict ratings

Using a unique German data set containing ratings and comments on doctors, we build a Binary Text Classifier. In part 1 we've introduced a complete machine learning work flow that predicts ratings from comments. In this second part, we improve on our baseline by implementing a LSTM neural network model and using FastText embeddings. Using Keras for feature creation and prediction, we improve on the ability to understand comment sentiments.

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Natural Language Processing of German texts - Part 1: Using machine-learning to predict ratings

Using a unique German data set containing ratings and comments on doctors, we build a Binary Text Classifier. To do so, we implement a complete machine learning work flow that predicts ratings from comments. In this first part, we start with basic methods. We go through text pre processing, feature creation (TF-IDF), classification and model optimization. Finally, we evaluate our model's ability to predict the sentiment of comments.

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