Next Word Prediction Using LSTM – Language Modeling on Shakespeare's Hamlet

Project: Hamlet Next Word Prediction using LSTM
Author: Shailesh Gupta
GitHub: View Source Code

📌 Overview

This deep learning project uses an LSTM (Long Short-Term Memory) network to perform next word prediction on a text corpus derived from Shakespeare's Hamlet. The model learns word sequences and generates text one word at a time, simulating the creative structure of natural language.

🎯 Problem Statement

Can a neural network trained on classical literature predict the next word in a sentence with contextual accuracy?

This project explores the ability of LSTM-based models to understand and generate language sequences from complex, stylized text.

🔍 Key Features

  • Text generation using LSTM layers in Keras
  • Custom tokenizer, sequence creation, and word embedding
  • Model trained on over 12,000 words from Shakespeare’s Hamlet
  • User input allows dynamic next-word prediction
  • Deployed as an interactive Streamlit app

🛠️ Tools & Tech Stack

  • Python, TensorFlow, Keras
  • LSTM layers for sequential prediction
  • NLTK, Regular Expressions (text cleaning)
  • Streamlit (for deployment)

📊 App Screenshot



📁 GitHub Repository

View the complete model training process, text generation logic, and UI code here:
github.com/sg2499/Hamlet-Next-Word-Prediction-LSTM

🌐 Live Demo

👉 Try the Next Word Predictor App

💡 What I Learned

  • How LSTM networks learn temporal word patterns in sequential text
  • The importance of padding, token indexing, and vocabulary control
  • Deploying a language generation model as an interactive tool

🙌 Stay Connected

If you liked this project, feel free to star the GitHub repo ⭐ or connect with me on LinkedIn.

More NLP and creative AI projects coming soon — stay tuned!

📌 Tags:

LSTM, Language Modeling, Next Word Prediction, NLP, Text Generation, Shakespeare, Deep Learning, Streamlit, Python, Keras, TensorFlow

Location: India

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