Machine learning: Practical applications
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Updated
Jan 7, 2022 - Jupyter Notebook
Machine learning: Practical applications
A bash script to scrap shakespeare works from shakespeare.mit.edu + Already scraped plays in txt format
Scrape Shakespeare from MIT
text-rnn allows you to create modern neural network architectures which use modern techniques such as skip-embedding and attention weighting. Train either a bidirectional or normal LSTM recurrent neural network to generate text using any dataset. You can continue training a pre-trained model.
SyllaBits is a web-based game that helps you learn, practice, and master the skill of scansion. Contributors: Elizabeth E. Tavares (principle investigator), Elijah Hilty (developer), Jeff Gray (co-investigator). Sponsors: Collaborative Arts research Institute, Hudson Strode Program in Renaissance Studies, University of Alabama.
My solution for TryRuby's "Noble Kinsmen" problem.
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.
GPTs trained with shakespeare dataset. Includes: small 10.8M GPT mimicking Andrej Karpathy's video lecture, Universal Transformer with Adaptive Computation Time
A character-level decoder Transformer that generates Shakespeare's like text.
Simple character level Transformer
Add a description, image, and links to the shakespeare-dataset topic page so that developers can more easily learn about it.
To associate your repository with the shakespeare-dataset topic, visit your repo's landing page and select "manage topics."