Alireza-Akhavan/rnn-notebooks
RNN(SimpleRNN, LSTM, GRU) Tensorflow2.0 & Keras Notebooks (Workshop materials)
This project provides practical, hands-on examples for anyone looking to understand and apply Recurrent Neural Networks (RNNs) in deep learning. You'll find Jupyter notebooks that take various sequence data like cryptocurrency prices, video frames, or text, and demonstrate how to build models to predict future values, classify movements, generate text, or translate languages. This resource is ideal for data scientists, machine learning engineers, and researchers who are learning or applying sequence modeling techniques.
112 stars.
Use this if you need to learn or implement deep learning models for sequence data tasks like time-series forecasting, video analysis, natural language processing, or machine translation.
Not ideal if you are looking for a pre-built, production-ready solution rather than educational materials and code examples.
Stars
112
Forks
46
Language
Jupyter Notebook
License
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Last pushed
Oct 23, 2025
Commits (30d)
0
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