AWS-Certified-Machine-Learning-Specialty Free Practice Test

A Data Scientist is developing a machine learning model to classify whether a financial transaction is fraudulent. The labeled data available for training consists of 100,000 non-fraudulent observations and 1,000 fraudulent observations.
The Data Scientist applies the XGBoost algorithm to the data, resulting in the following confusion matrix when the trained model is applied to a previously unseen validation dataset. The accuracy of the model is 99.1%, but the Data Scientist has been asked to reduce the number of false negatives.

Which combination of steps should the Data Scientist take to reduce the number of false positive predictions by the model? (Select TWO.)

1. A. Change the XGBoost eval_metric parameter to optimize based on rmse instead of error.
2. B. Increase the XGBoost scale_pos_weight parameter to adjust the balance of positive and negative weights.
3. C. Increase the XGBoost max_depth parameter because the model is currently underfitting the data.
4. D. Change the XGBoost evaljnetric parameter to optimize based on AUC instead of error.
5. E. Decrease the XGBoost max_depth parameter because the model is currently overfitting the data.

Correct Answer: DE

A large company has developed a B1 application that generates reports and dashboards using data collected from various operational metrics The company wants to provide executives with an enhanced experience so they can use natural language to get data from the reports The company wants the executives to be able ask questions using written and spoken interlaces
Which combination of services can be used to build this conversational interface? (Select THREE )

1. A. Alexa for Business
2. B. Amazon Connect
3. C. Amazon Lex
4. D. Amazon Poly
5. E. Amazon Comprehend
6. F. Amazon Transcribe

Correct Answer: BEF

A Data Scientist is building a model to predict customer churn using a dataset of 100 continuous numerical features. The Marketing team has not provided any insight about which features are relevant for churn prediction. The Marketing team wants to interpret the model and see the direct impact of relevant features on the model outcome. While training a logistic regression model, the Data Scientist observes that there is a wide gap between the training and validation set accuracy.
Which methods can the Data Scientist use to improve the model performance and satisfy the Marketing team’s needs? (Choose two.)

1. A. Add L1 regularization to the classifier
2. B. Add features to the dataset
3. C. Perform recursive feature elimination
4. D. Perform t-distributed stochastic neighbor embedding (t-SNE)
5. E. Perform linear discriminant analysis

Correct Answer: BE

A machine learning specialist is developing a proof of concept for government users whose primary concern is security. The specialist is using Amazon SageMaker to train a convolutional neural network (CNN) model for a photo classifier application. The specialist wants to protect the data so that it cannot be accessed and transferred to a remote host by malicious code accidentally installed on the training container.
Which action will provide the MOST secure protection?

1. A. Remove Amazon S3 access permissions from the SageMaker execution role.
2. B. Encrypt the weights of the CNN model.
3. C. Encrypt the training and validation dataset.
4. D. Enable network isolation for training jobs.

Correct Answer: D

A retail company is using Amazon Personalize to provide personalized product recommendations for its customers during a marketing campaign. The company sees a significant increase in sales of recommended items to existing customers immediately after deploying a new solution version, but these sales decrease a short time after deployment. Only historical data from before the marketing campaign is available for training.
How should a data scientist adjust the solution?

1. A. Use the event tracker in Amazon Personalize to include real-time user interactions.
2. B. Add user metadata and use the HRNN-Metadata recipe in Amazon Personalize.
3. C. Implement a new solution using the built-in factorization machines (FM) algorithm in Amazon SageMaker.
4. D. Add event type and event value fields to the interactions dataset in Amazon Personalize.

Correct Answer: A