Neural Network Tutorials - Herong's Tutorial Examples
∟RNN (Recurrent Neural Network)
This chapter provides introductions and tutorials on RNN (Recurrent Neural Network). Topics include introduction to the classical RNN model, LSTM (Long Short-Term Memory) model, GRU (Gated Recurrent Unit) model.
What Is RNN (Recurrent Neural Network)
RNN Recursive Function
What Is LSTM (Long Short-Term Memory)
What Is GRU (Gated Recurrent Unit)
Takeaways:
- RNN (Recurrent Neural Network) uses a recursive function to
carry a state vector from one sample to the next sample.
This is to help capture dependences between samples in a sequential sample set.
- LSTM (Long Short-Term Memory) is an enhancement of the RNN that
two state vectors, s representing the short-term memory and l representing long-term memory.
- GRU (Gated Recurrent Unit) is a simplified version of the LSTM that
uses only one state vector and two gate vectors, reset gate and update gate.
Table of Contents
About This Book
Deep Playground for Classical Neural Networks
Building Neural Networks with Python
Simple Example of Neural Networks
TensorFlow - Machine Learning Platform
PyTorch - Machine Learning Platform
Gradio - ML Demo Platform
CNN (Convolutional Neural Network)
►RNN (Recurrent Neural Network)
GNN (Graph Neural Network)
GAN (Generative Adversarial Network)
Performance Evaluation Metrics
References
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