Basics of Deep Learning

What are Transformers known for?

• They are primarily used for image processing tasks.

• They are state-of-the-art for NLP, vision, etc., and use self-attention mechanisms.

• They are mainly used for traditional programming tasks.

• They are known for their ability to perform arithmetic calculations.

What are Convolutional Neural Networks (CNNs) specialized for?

• They are specialized for images.

• They are specialized for text processing.

• They are specialized for audio recognition.

• They are specialized for time series analysis.

How does a neural network process input data?

• Input data is fed into a neural network, where each neuron computes a weighted sum of its inputs, applies a non-linear activation function, and passes it on.

• Input data is directly outputted without any processing by the neural network.

• Input data is converted into binary format and stored in memory without any computation.

• Input data is processed by a single neuron that outputs the final result.

Name some tools and libraries for deep learning.

• Scikit-learn

• TensorFlow

• Pandas

• NumPy

What is the key idea of Deep Learning?

• Learn features automatically from raw data, instead of hand-crafting them.

• Manually design features for data analysis.

• Use traditional machine learning algorithms exclusively.

• Focus on shallow neural networks for data processing.

What is the role of activation functions in a neural network?

• They add non-linearity to the model.

• They increase the number of layers in the network.

• They reduce the training time of the model.

• They improve the accuracy of the model without any data preprocessing.

What type of data are Recurrent Neural Networks (RNNs) used for?

• Image data like photographs

• Sequence data like text or time series

• Static data like spreadsheets

• Graph data like social networks

What is Deep Learning?

• Deep Learning is a subfield of machine learning that uses artificial neural networks with many layers to learn representations from data.

• Deep Learning is a technique that involves using decision trees to classify data.

• Deep Learning is a method of data analysis that relies on linear regression models.

• Deep Learning is a process of manually coding rules for data interpretation.

What are Feedforward Neural Networks (MLP) good for?

• They are good for image recognition.

• They are good for tabular data.

• They are good for natural language processing.

• They are good for time series forecasting.

What is the purpose of weights and biases in a neural network?

• They are parameters the network learns to minimize errors.

• They are used to initialize the network's architecture.

• They help in increasing the network's complexity.

• They are responsible for the network's activation functions.