In the context of neural networks, what does the term "backpropagation" refer to?
- Training a model using historical data
- Forward pass computation
- Adjusting the learning rate
- Updating model weights
"Backpropagation" in neural networks refers to the process of updating the model's weights based on the computed errors during the forward pass. It's a key step in training neural networks and involves minimizing the loss function.
Loading...
Related Quiz
- You're building a system that needs to store vast amounts of unstructured data, like user posts, images, and comments. Which type of database would be the best fit for this use case?
- While training a deep neural network for a regression task, the model starts to memorize the training data. What's a suitable approach to address this issue?
- In Cassandra, data retrieval is fast because it uses a _______ based data model.
- In Data Science, when dealing with large datasets that do not fit into memory, the Python library _______ can be a useful tool for efficient computations.
- In unsupervised learning, _______ is a method where the objective is to group similar items into sets.