Network Analysis of Shakespeare plays
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Updated
Mar 30, 2017 - Jupyter Notebook
Network Analysis of Shakespeare plays
Dynamic Shakespeare Character Sentiment Analysis
This is a TF-IDF calculator for shakespearean play dataset
Generates shakespeare style play by LSTM (RNN) network.
Graphs the level of emotion over time in a piece of literature to help visualise the story arc.
DNN, CNN and RNN in tensorflow.. DNN and CNN have upto 99% test accuracy.. The trained RNN(GRU) generates random Shakespeare plays...
All of Shakespeare's texts from the first folio edition with an interactive dictionary to help comprehension.
Built Classification models to determine the player from Shakespeare-plays dataset using Feature Engineering and exploratory data analysis.
A bash script to scrap shakespeare works from shakespeare.mit.edu + Already scraped plays in txt format
Text and cleaning code for shakespeare ai app.
Web interface to interact with my Shakespeare GPT-2 model to generate lines based on any chosen Shakespeare play.
Code and data for extracting co-occurrence networks from Shakespeare's plays
Char-level language model on Shakespeare's writings
Shows the year(s) written, genre, and number of speeches for each of Shakespeare's plays. Built on Open Source Shakespeare's list of Shakespeare's plays by number of speeches.
Auto-generated text based on Shakespeare poetry
Text generator based on markov chains, implemented in python (just for fun)
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