2. Deep Learning with TensorFlow 2.x (Chapter 2)

Section 2 of 4-~ 2 min read-Synced from Cuantum content

1. What is eager execution in TensorFlow 2.x? - a) A mode where TensorFlow operations are executed lazily to optimize performance.

b) A mode where TensorFlow operations are executed immediately, making it easier to debug and develop models interactively.
c) A special mode for GPU acceleration in TensorFlow.
d) A mode where operations are executed only after calling the tf.run() function.

1. In TensorFlow 2.x, which API is typically used for building deep learning models? - a) Estimator API

b) Dataset API
c) Keras API
d) Sequential API

1. Which of the following is NOT a common use case for pretrained models from TensorFlow Hub? - a) Image classification

b) Object detection
c) Reinforcement learning
d) Text embedding

1. What is the primary advantage of using TensorFlow Serving in production? - a) It allows deploying machine learning models as scalable web services.

b) It is a tool for optimizing hyperparameters during model training.
c) It is used for monitoring the performance of models during training.
d) It improves the accuracy of models during training by fine-tuning.