Time Series Prediction and Text Generation

Submission Files

The submission includes all required file RNN_project_student_version.ipynb All code must be written ONLY in the TODO sections and no previous code should be modified.

Window time series data.

The submission returns the proper windowed version of input time series of proper dimension listed in the notebook.

Build an RNN model to perform regression.

The submission constructs an RNN model in keras with LSTM module of dimension defined in the notebook.

Find and remove all non-english or punctuation characters from input text data.

The submission removes all non-english / non-punctuation characters. (English characters should include string.ascii_lowercase and punctuation includes [' ', '!', ',', '.', ':', ';', '?'] (space, exclamation mark, comma, period, colon, semicolon, question mark))

Implement a function to window input text data

The submission returns the proper windowed version of input text of proper dimension listed in the notebook.

Build an RNN model to perform multiclass classification.

The submission constructs an RNN model in keras with LSTM module of dimension defined in the notebook.

Generate text using a trained RNN classifier.

The submission presents examples of generated text from a trained RNN module. The majority of this generated text should consist of real english words.