These are my ongoing practical works for the Oxford’s Course Deep Learning for Natural Language Processing (2017). It is focused on performing task based text embedding i.e., learning word embed vectors while performing text classification. The text classification are done using NN, LSTM and Bi-Directional LSTM using tensorflow. As well as embedded word vector visualisation using T-SNE.
I have provided my inferences within the notebook.

Dataset: TED dataset (Textual content) - Multiclass classification.

All the practicals are done in Tensorflow