Which of the following statements is false?
A) Keras facilitates experimenting with many deep-learning models and tweaking them in various ways until you find the models that perform best for your applications.
B) Deep learning works well only when you have lots of data.
C) Transfer learning uses existing knowledge from a previously trained model as the foundation for a new model.
D) Data augmentation adds data to a dataset by deriving new data from existing data. For example, in an image dataset, you might rotate the images left and right so the model can learn about objects in different orientations.

Question

Quizplus · Accepted Answer

While having more data can certainly help improve the performance of a deep learning model, there are techniques such as transfer learning and data augmentation that can help compensate for smaller datasets. Therefore, it is not necessarily true that deep learning works well only with lots of data.

Which of the Following Statements Is False