Deep Learning and AI SuperheroChapter 42

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

Section 2 of 4-~ 12 min read-Synced from Cuantum content
  1. What is eager execution in TensorFlow 2.x?
  2. - 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?
  2. - 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?
  2. - a) Image classification
  • b) Object detection
  • c) Reinforcement learning
  • d) Text embedding
  1. What is the primary advantage of using TensorFlow Serving in production?
  2. - 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.