QUESTION: 13

The displayed graph is from a forecasting model for testing a time series.

Considering the graph only, which conclusion should a Machine Learning Specialist make about the behavior of the model?

The model predicts both the trend and the seasonality well
The model predicts the trend well, but not the seasonality.
The model predicts the seasonality well, but not the trend.
The model does not predict the trend or the seasonality well.

Answer(s): A

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A company wants to classify user behavior as either fraudulent or normal. Based on internal research, a Machine Learning Specialist would like to build a binary classifier based on two features: age of account and transaction month. The class distribution for these features is illustrated in the figure provided.

Based on this information, which model would have the HIGHEST accuracy?

Long short-term memory (LSTM) model with scaled exponential linear unit (SELU)
Logistic regression
Support vector machine (SVM) with non-linear kernel
Single perceptron with tanh activation function

Answer(s): C

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QUESTION: 15

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 (PII).

The dataset:
•Must be accessible from a VPC only.
•Must not traverse the public internet.

How can these requirements be satisfied?

Create a VPC endpoint and apply a bucket access policy that restricts access to the given VPC endpoint and the VPC.
Create a VPC endpoint and apply a bucket access policy that allows access from the given VPC endpoint and an Amazon EC2 instance.
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.
Create a VPC endpoint and use security groups to restrict access to the given VPC endpoint and an Amazon EC2 instance

Answer(s): A

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QUESTION: 16

During mini-batch training of a neural network for a classification problem, a Data Scientist notices that training accuracy oscillates.

What is the MOST likely cause of this issue?

The class distribution in the dataset is imbalanced.
Dataset shuffling is disabled.
The batch size is too big.
The learning rate is very high.

Answer(s): D

Reference:

https://towardsdatascience.com/deep-learning-personal-notes-part-1-lesson-2-8946fe970b95

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