A00-406 Sample Practice Exam Questions 2024 Updated Verified [Q49-Q66]

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A00-406 Sample Practice Exam Questions 2024 Updated Verified

Exam Study Guide Free Practice Test LAST UPDATED A00-406

NO.49 Which algorithm is commonly used for binary classification in machine learning pipelines, especially when dealing with imbalanced datasets?

Linear Regression

K-Means Clustering

Support Vector Machine (SVM)

Principal Component Analysis (PCA)

NO.50 What is the primary goal of hyperparameter tuning during model building?

To increase model complexity

To add more features to the model

To optimize the settings that control the model’s learning process

To improve data preprocessing techniques

NO.51 Which of the following is NOT a common data format for exchanging data between systems?

CSV (Comma-Separated Values)

JSON (JavaScript Object Notation)

HTML (Hypertext Markup Language)

SQL (Structured Query Language)

NO.52 In the context of data sources, what is ETL?

Extract, Transform, Load

Efficient Text Link

Examine, Test, Log

Execute, Terminate, Launch

NO.53 What is the purpose of regularization techniques in model building, such as L1 and L2 regularization?

To increase model complexity

To add more features to the model

To prevent overfitting and reduce model complexity

To speed up model training

NO.54 In model evaluation, what is the purpose of a ROC curve (Receiver Operating Characteristic)?

To visualize data distribution

To compare models’ performance in terms of sensitivity and specificity

To evaluate the mean squared error of a model

To measure feature importance

NO.55 What is the primary role of a data warehouse in an organization?

Real-time data analysis

Long-term data storage and analysis

Data exploration and visualization

Data transformation and cleaning

NO.56 What is the purpose of cross-entropy loss in machine learning, especially in the context of classification?

To calculate the mean squared error of a regression model

To measure the dissimilarity between predicted and actual class probabilities

To quantify the variance of a model

To evaluate feature importance

NO.57 What does API stand for in the context of data sources?

Application Programming Interface

Advanced Programming Integration

Automated Program Integration

Application Program Interface

NO.58 Which type of data source typically stores structured data in a tabular format?

NoSQL databases

APIs

Relational databases

Text documents

NO.59 What is the main advantage of using a RESTful API (Representational State Transfer) as a data source?

Real-time data processing

Support for complex data structures

Simple and standardized communication

High security features

NO.60 Which of the following is a common technique for handling missing data in a machine learning pipeline?

Ignoring missing data

Replacing missing values with zeros

Imputing missing values

Deleting rows with missing data

NO.61 Which of the following best describes unstructured data?

Data that is organized in rows and columns

Data that is difficult to process and lacks a predefined structure

Data stored in a relational database

Data with a clear schema

NO.62 Which type of model is typically used for time-series forecasting?

Decision Trees

Logistic Regression

AutoRegressive Integrated Moving Average (ARIMA)

K-Means Clustering

NO.63 In the context of data integration, what does “data transformation” refer to?

Extracting data from source systems

Storing data in a centralized repository

Converting and reshaping data to match the target schema

Backing up data for disaster recovery

NO.64 What is the main goal of data preprocessing in a machine learning pipeline?

To train the model

To remove irrelevant features

To prepare the data for analysis and modeling

To visualize the data

NO.65 Which machine learning technique is typically used for building a model to predict a numeric target variable?

Classification

Regression

Clustering

Dimensionality reduction

NO.66 What is the primary role of a loss function in model training?

To maximize the model’s performance

To assess the accuracy of the model

To measure the difference between predicted and actual values

To visualize the data

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A00-406 Sample Practice Exam Questions 2024 Updated Verified [Q49-Q66]

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