A collection of notebooks for projects focused on natural language processing problems. They make opinionated use of TensorFlow (particularly its Keras API) to create Embeddings Layers and Recurrent Neural Networks (RNNs). They rely on openenly available data so that they can be easily reproduced.
The following is a brief summary of the projects available.
- Word embedding: creates an embedding for a sentiment classification task which can be visualized in Embedding Projector. An embedding is a dense vector of floating point values that are the weights learned by the model during training. In this example the embedding is built against the openly available IMDb movie review dataset.
Use pre-trained GloVe word embeddings to improve sentiment detection on the IMDb movie review dataset.