Class 2: Deep Learning Frameworks

Test your knowledge by answering the following questions:

Time Remaining: 03:20

1. Which framework is developed by Google for deep learning?

A) PyTorch B) TensorFlow C) Keras D) Theano

2. What is a tensor in the context of deep learning frameworks?

A) A variable type for storing integers only B) A multi-dimensional array used in computations C) A linear regression model D) A type of activation function

3. Which framework is developed by Facebook for deep learning?

A) TensorFlow B) PyTorch C) Keras D) MXNet

4. Which deep learning framework acts as a high-level API over TensorFlow?

A) Keras B) PyTorch C) Caffe D) Theano

5. What is a computational graph in deep learning?

A) A data structure representing operations as nodes B) A tool for data visualization C) A way to represent linear models D) A neural network optimizer

6. Which framework provides both high-level and low-level APIs?

A) PyTorch B) TensorFlow C) Keras D) MXNet

7. Which API type is typically easier for beginners to use in deep learning?

A) Low-Level API B) High-Level API C) Complex-Level API D) Intermediate-Level API

8. How can you install TensorFlow using pip?

A) pip install tf B) pip install tensorflow C) pip install tflearn D) pip install keras-tf

9. Which library integrates seamlessly with TensorFlow for building models?

A) PyTorch B) Keras C) Caffe D) Theano

10. Which deep learning framework is known for dynamic computation graphs?

A) TensorFlow B) PyTorch C) Keras D) MXNet