In transfer learning, what is the process of updating the weights of the pre-trained model with new data called?
- Feature Engineering
- Fine-Tuning
- Data Augmentation
- Model Stacking
In transfer learning, fine-tuning is the process of updating the weights of a pre-trained model with new data. This allows the model to adapt to the specific characteristics of the new data while leveraging the knowledge learned from the pre-training on a different but related task.
Loading...
Related Quiz
- In the context of model deployment, _______ is the process of ensuring the model's predictions remain consistent and accurate over time.
- When normalizing a database in SQL, separating data into two tables and creating a new primary and foreign key relationship is part of the _______ normal form.
- The process of adjusting the contrast or brightness of an image is termed as _______ in image processing.
- 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 the context of Data Science, which tool is most commonly used for data manipulation and analysis due to its extensive libraries and ease of use?