CaptainE/RNN-LSTM-in-numpy
Building a RNN and LSTM from scratch with NumPy.
This project helps deep learning students and researchers understand how recurrent neural networks (RNNs) and Long Short-Term Memory (LSTM) networks process sequential data. It takes in simple sequences of characters and outputs predictions for the next character, demonstrating the internal workings of these models. This is for individuals learning or teaching the foundational mechanics of deep learning models for sequence prediction.
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Use this if you are studying or teaching the core principles of RNNs and LSTMs and need a hands-on, step-by-step implementation from scratch to grasp their internal mechanics.
Not ideal if you need to build or apply a production-ready sequence prediction model for a real-world dataset, as this is an educational implementation focused on learning.
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Jupyter Notebook
License
GPL-3.0
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Last pushed
Jun 27, 2024
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