One of the challenges in training deep RNNs is the ________ gradient problem, which affects the network's ability to learn long-range dependencies.
- Vanishing
- Exploding
- Overfitting
- Regularization
The vanishing gradient problem refers to the issue where gradients in deep RNNs become too small during training, making it challenging to capture long-range dependencies.
Loading...
Related Quiz
- In which learning approach does the model learn to...
- A bank uses a machine learning model for loan approvals. However, it's observed that individuals from certain ethnic backgrounds are consistently getting rejected more than others, despite having similar financial profiles. This raises concerns related to which aspect of machine learning?
- Time series forecasting is crucial in fields like finance and meteorology because it helps in predicting stock prices and ________ respectively.
- Which technique involves setting a fraction of input units to 0 at each update during training time, which helps to prevent overfitting?
- How do the generator and discriminator components of a GAN interact during training?