You work as a machine learning specialist for a security company that uses video feeds to identify criminal activity in a client company’s retail environments. You are building a convolutional neural network model using TensorFlow to use for your video classification. The model is expected to classify video scenes as criminal, such as theft, or benign. You have thousands of hours of video on which to train your model. Therefore, you plan to leverage hyperparameter tuning to run multiple training jobs using different hyperparameter combinations. The goal is to find the model with the best training result. You are writing your hyperparameter tuning job in your SageMaker jupyter notebook. When you create your HyperparameterTuner object in your python code, which parameters do you pass in the method? (Select TWO)

Answer options:

A.TensorFlow estimator
B.Training steps
C.Evaluation steps
D.Hyperparameter ranges
E.Instance type

Correct Answers: A and D
Option A is correct. When you create the HyperparameterTuner object in your python code, you need to specify the estimator you are using, in this case, TensorFlow, the ranges for your hyperparameters, the objective metric you wish to solve to, and resource configuration details, such as the number of training jobs to run in total and how many training jobs can be run in parallel.
Option B is incorrect. You specify the training steps when you create your TensorFlow estimator in your python code.
Option C is incorrect. You specify the evaluation steps when you create your TensorFlow estimator in your python code.
Option D is correct. When you create the HyperparameterTuner object in your python code, you need to specify the estimator you are using, in this case, TensorFlow, the ranges for your hyperparameters, the objective metric you wish to solve to, and resource configuration details, such as the number of training jobs to run in total and how many training jobs can be run in parallel.
Option E is incorrect. You specify the instance type when you create your TensorFlow estimator in your python code.
References:
Please see the Amazon SageMaker page titled Machine learning for every developer and data scientist (https://aws.amazon.com/machine-learning/accelerate-amazon-sagemaker/#Train_machine_learning_models),
The Amazon SageMaker Examples titled Hyperparameter Tuning using SageMaker Tensorflow Container (https://github.com/aws/amazon-sagemaker-examples/blob/master/hyperparameter_tuning/tensorflow_mnist/hpo_tensorflow_mnist.ipynb),
The Medium article titled Video Classification using CNNs (https://medium.com/analytics-vidhya/video-classification-using-cnns-db18bd2b7e72)