Build an AI Storyteller from Scratch | Character-Level Text Generation with RNN in PyTorch

Описание: In this exciting project, we build a character-level text generation model using Recurrent Neural Networks (RNN) in PyTorch. This is a beginner-friendly deep learning project that focuses on natural language processing (NLP), sequence modeling, and the fundamentals of RNN-based text generation.

You’ll learn how to prepare and process a simple but slightly complex English story corpus, convert characters to numerical format, and create a dataset suitable for training a recurrent model. Then, we define a custom RNN model using PyTorch’s nn.RNN class, followed by training it on our dataset to learn language patterns.

Once training is complete, we’ll generate new text character by character, mimicking the style of our input story. This is a great introduction to how AI models like GPT started—with character-level generation before progressing to word-level and transformer-based architectures.

By the end of this tutorial, you’ll understand:

How to build datasets for sequence prediction

How RNNs learn temporal patterns in text

How to implement and train an RNN in PyTorch

How to generate synthetic text using a trained model

How to interpret and evaluate AI-generated sequences

Whether you're a student, hobbyist, or aspiring ML engineer, this project will give you hands-on experience with foundational NLP concepts. No massive datasets required—just a bit of creativity and curiosity!

🔥 This project is perfect if you’re looking to:

Work with limited data

Understand how RNNs work under the hood

Start your journey into AI text generation

Build cool story-generating bots