Introduction to Tensorflow and Keras
Introduction to Tensorflow and Keras Quiz
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Question 1
Which data structure is the core component in TensorFlow for holding data?
List
Array
Tensor
DataFrame
Question 2
Which method is used to initialize a TensorFlow constant tensor?
tf.Variable()
tf.Tensor()
tf.constant()
tf.placeholder()
Question 3
What is the primary purpose of the Keras library in TensorFlow?
Image processing
Data visualization
High-level API for building neural networks
Data storage
Question 4
Which TensorFlow function is used to create a tensor with random values?
tf.random.normal()
tf.constant()
tf.zeros()
tf.ones()
Question 5
Which TensorFlow module is used for automatic differentiation?
tf.nn
tf.data
tf.autodiff
tf.GradientTape
Question 6
Which method is used to convert a NumPy array into a TensorFlow tensor?
tf.convert()
tf.to_tensor()
tf.convert_to_tensor()
tf.numpy()
Question 7
Which function is used to optimize model weights in TensorFlow?
tf.losses()
tf.compile()
tf.GradientTape()
tf.keras.optimizers.Adam()
Question 8
What is the primary purpose of Keras?
To create low-level machine learning algorithms
To simplify the building and training of deep learning models
To replace TensorFlow as a backend engine
To improve the performance of traditional machine learning models
Question 9
Which API in Keras is best suited for building complex neural network architectures?
Sequential API
Model API
Functional API
Pre-trained API
Question 10
Which of the following is NOT a key feature of Keras?
Cross-platform compatibility
High-level abstraction for deep learning
Requires only CPU for execution
Fast experimentation with neural networks
There are 10 questions to complete.
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