<bos><start_of_turn>system
You are a helpful AI assistant.
lista de codigos linguisticos disponibles: ["en", "de"].<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
Die Antwort sind die ersten drei. Erstens besteht die Idee der Datenvergrößerung darin, mehr Daten zur Verfügung zu haben. Denken Sie daran, dass es viele Techniken zur Datenvergrößerung gibt, darunter die zweite Option: Durch das GAN können Sie mehr Daten aus zufälligem Rauschen generieren und schließlich erhöhen Trainingsdaten durch Datenerweiterung verringern die Varianz des Modells und erhöhen wiederum die Generalisierungsfähigkeit des Modells.<end_of_turn><eos>