How to Optimize an RNN in PyTorch (~20% to over 80% accuracy)

Описание к видео How to Optimize an RNN in PyTorch (~20% to over 80% accuracy)

You can change the hyperparameters and architecture of your RNN to get a more accurate model. Takeaways:
- Batch Size affects how much data the network sees before updating its weights
- Learning rate affects how quickly your network converges on the optimal weights
- RNNs can take different input sizes, play around with how you input your data as well to reach an optimal point

Former Video:    • First Attempt to Make an RNN Work on ...  

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