1.What is a neural network with many layers called?
A: A deep neural network
2. What challenge is commonly associated with deep learning models compared to traditional machine learning models?
A: They are often considered “black boxes” due to lack of interpretability
3. In which area is Deep Learning commonly applied?
A; Image and speech recognition
4. What is a primary advantage of deep learning over traditional machine learning?
A: Automatically extracts features from raw data
5. Neural Networks are inspired by which part of the human body?
A: The brain
6. What does CNN stand for in the context of deep learning
A: Convolutional Neural Network
7. What role do GPUs play in Deep Learning?
A: They accelerate computations in neural networks
8. What type of network is commonly used for image recognition?
A: Convolutional Neural Networks
9. Which of the following is an important challenge in Deep Learning?
A: Overfitting
10. Which type of neural network is commonly used for time series data or sequential tasks?
A: Recurrent Neural Network
11. What is an Activation Function in a neural network?
A: A mathematical function that determines the output of a neuron
12. Which of the following is a key characteristic that differentiates deep learning from traditional machine learning?
A: Use of artificial neural networks with multiple layers
13. Which of the following is an application of Convolutional Neural Networks (CNNs)?
A: Image recognition
14. Which neural network architecture is best suited for processing sequential data like text or time series?
A: Recurrent Neural Networks (RNNs)
15. In a Generative Adversarial Network (GAN), what is the role of the generator?
A: To generate synthetic data resembling real data
16. How do neurons in a Neural Network communicate?
A: Through connections between neurons
17.What is the main advantage of using Deep Learning?
A: It can solve complex problems by learning from large datasets
18. What is overfitting in neural networks?
A: When a model is too complex and fits the training data too closely
19. When did Deep Learning become powerful?
A: In the last 10-15 years
20. Which of the following best describes Deep Learning?
A: Teaching a computer to recognize patterns
21. Which of these is a commonly used activation function in neural networks?
A: ReLU
22. Which type of neural network is commonly used for time series data or sequential tasks?
A: Recurrent Neural Network
23. Which concept allows Neural Networks to continue learning from complex, large datasets?
A: Backpropagation
24. What is the purpose of the “loss function” in a neural network?
A: To measure the difference between the predicted output and the actual result
25. Who introduced the least squares method in 1805, contributing to the foundation of machine learning?
A: Adrien-Marie Legendre
26. What are the basic units in a Neural Network called?
A: Neurons
27. Which algorithm is commonly used to update the weights in a neural network?
A: Gradient Descent