<bos><start_of_turn>system
You are a helpful AI assistant.
lista de codigos linguisticos disponibles: ["en", "en"].<end_of_turn>
<start_of_turn>user
Given the following text, answer which are the correct answers:

Amara is writing a script for a YouTube video about data augmentation.
She wants to cover some of the most critical aspects of using the technique on an image data set.
This is Amara's list of the key points she wants to leave with her audience.

Which of the following statements would you let Amara share with her audience?
A) Through data augmentation, we can artificially increase the amount of data by generating new samples from existing data.
B) Generative Adversarial Networks (GAN) and style transfer are advanced techniques that can help increase data.
C) Data augmentation has a regularization effect when it is used to increase the amount of data before training a model.
D) Data augmentation always eliminates biases present in the original data.<end_of_turn>
<start_of_turn>model
The answer is the first three. First, the idea of ​​increasing the data is to have more data available, remember that there are many techniques for increasing data, among them is the second option, through the GAN you can generate more data from random noise, and finally Increasing the training data through data augmentation decreases the variance of the model and, in turn, increases the generalization ability of the model.<end_of_turn><eos>