Home » Introduction to TensorFlow » Choose the correct workflow to serve your model in the cloud Choose the correct workflow to serve your model in the cloud Serving Models in the Cloud >>> Choose the correct workflow to serve your model in the cloud >>> Introduction to TensorFlow 1. Question 1 Choose the correct workflow to serve your model in the cloud. 1 / 1 point Create the model —> save your model –> serve your model Create the model —> train and evaluate your model –> save your model –> serve your model Create the model —> save your model –> train and evaluate your model –> serve your model None of the above. =========================================== 4. Question 4 Which of the following statements is true? 1 / 1 point SavedModel is a universal serialization format for TensorFlow models. SavedModel provides a “language neutral format” to save your machine learning models that is both recoverable and hermetic. SavedModel is a proprietary serialization format for TensorFlow models. SavedModel provides a “proprietary language protocol” to save your machine learning models that is both recoverable and hermetic. Both A and B None of the above =========================================== 2. Question 2 Which statement is true? 1 / 1 point To serve our model for others to use, we export the model file and deploy the model as a service. To serve our model for others to use, we zip the model file and deploy the model as a JSON request. Both A & B None of the above. =========================================== 3. Question 3 Which statement is true? 1 / 1 point Export model to a TensorFlow ZippedModel format to serve your model. tf.saved_model.save –> zips a model file object to a SavedModel format. (EXPORT_PATH) is the directory in which to write the SavedModel. None of the above. Other Questions Of This Category Which of the following statements is true of TensorFlowThe Keras Functional API provides which of the followingSelect the correct statement regarding the Keras Functional APIWhich are useful components when building custom Neural Network modelsWhich of the following is a type of feature columnThe activations in regularization is scaled by which of the followingWhich model is appropriate for a plain stack of layersNon linearity helps in training your model at a much faster rate and with more accuracy without the loss of your important informationWhat operations can be performed on tensorsWhat are distinct ways to create a dataset
