<bos><start_of_turn>system
You are a helpful AI assistant.
lista de codigos linguisticos disponibles: ["en", "fr"].<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
La réponse est les trois premiers. Premièrement, l'idée d'augmenter les données est d'avoir plus de données disponibles, rappelez-vous qu'il existe de nombreuses techniques pour augmenter les données, parmi lesquelles se trouve la deuxième option, grâce au GAN, vous pouvez générer plus de données à partir du bruit aléatoire, et enfin augmenter le la formation des données via l'augmentation des données diminue la variance du modèle et, à son tour, augmente la capacité de généralisation du modèle.<end_of_turn><eos>