MLS-C01 Free Practice Test

A manufacturing company has structured and unstructured data stored in an Amazon S3 bucket A Machine Learning Specialist wants to use SQL to run queries on this data. Which solution requires the LEAST effort to be able to query this data?

1. A. Use AWS Data Pipeline to transform the data and Amazon RDS to run queries.
2. B. Use AWS Glue to catalogue the data and Amazon Athena to run queries
3. C. Use AWS Batch to run ETL on the data and Amazon Aurora to run the quenes
4. D. Use AWS Lambda to transform the data and Amazon Kinesis Data Analytics to run queries

Correct Answer: D

A Machine Learning Specialist at a company sensitive to security is preparing a dataset for model training. The dataset is stored in Amazon S3 and contains Personally Identifiable Information (Pll). The dataset:
* Must be accessible from a VPC only.
* Must not traverse the public internet. How can these requirements be satisfied?

1. A. Create a VPC endpoint and apply a bucket access policy that restricts access to the given VPC endpoint and the VPC.
2. B. Create a VPC endpoint and apply a bucket access policy that allows access from the given VPC endpoint and an Amazon EC2 instance.
3. C. Create a VPC endpoint and use Network Access Control Lists (NACLs) to allow traffic between only the given VPC endpoint and an Amazon EC2 instance.
4. D. Create a VPC endpoint and use security groups to restrict access to the given VPC endpoint and an Amazon EC2 instance.

Correct Answer: B

A Machine Learning Specialist is building a model to predict future employment rates based on a wide range of economic factors While exploring the data, the Specialist notices that the magnitude of the input features vary greatly The Specialist does not want variables with a larger magnitude to dominate the model
What should the Specialist do to prepare the data for model training'?

1. A. Apply quantile binning to group the data into categorical bins to keep any relationships in the data by replacing the magnitude with distribution
2. B. Apply the Cartesian product transformation to create new combinations of fields that are independent of the magnitude
3. C. Apply normalization to ensure each field will have a mean of 0 and a variance of 1 to remove any significant magnitude
4. D. Apply the orthogonal sparse Diagram (OSB) transformation to apply a fixed-size sliding window to generate new features of a similar magnitude.

Correct Answer: C

An insurance company is developing a new device for vehicles that uses a camera to observe drivers' behavior and alert them when they appear distracted The company created approximately 10,000 training images in a controlled environment that a Machine Learning Specialist will use to train and evaluate machine learning models
During the model evaluation the Specialist notices that the training error rate diminishes faster as the number of epochs increases and the model is not accurately inferring on the unseen test images
Which of the following should be used to resolve this issue? (Select TWO)

1. A. Add vanishing gradient to the model
2. B. Perform data augmentation on the training data
3. C. Make the neural network architecture complex.
4. D. Use gradient checking in the model
5. E. Add L2 regularization to the model

Correct Answer: BD

This graph shows the training and validation loss against the epochs for a neural network The network being trained is as follows
• Two dense layers one output neuron
• 100 neurons in each layer
• 100 epochs
• Random initialization of weights

Which technique can be used to improve model performance in terms of accuracy in the validation set?

1. A. Early stopping
2. B. Random initialization of weights with appropriate seed
3. C. Increasing the number of epochs
4. D. Adding another layer with the 100 neurons

Correct Answer: D