Which type of database is ideal for handling hierarchical data and provides better scalability, MongoDB or MySQL?
- MongoDB
- MySQL
- Both MongoDB and MySQL
- Neither MongoDB nor MySQL
MongoDB is a NoSQL database that is ideal for handling hierarchical data and provides better scalability for unstructured data. MongoDB uses BSON (Binary JSON) format, which makes it a good choice for applications that require flexibility and scalability in dealing with complex data structures.
A company uses an AI model for recruitment, and it's observed that the model is selecting more male candidates than female candidates for a tech role, even when both genders have similar qualifications. What ethical concern does this scenario highlight?
- Data bias in AI
- Lack of transparency in AI
- Data security and privacy issues in AI
- Ethical AI governance and accountability
This scenario highlights the ethical concern of "Data bias in AI." The AI model's biased selection towards male candidates indicates that the training data may be biased, leading to unfair and discriminatory outcomes. Addressing data bias is essential to ensure fairness and diversity in AI-driven recruitment.
Which algorithm would you use when you have a mix of input features (both categorical and continuous) and you need to ensure interpretability of the model?
- Random Forest
- Support Vector Machines (SVM)
- Neural Networks
- Naive Bayes Classifier
Random Forest is a suitable choice for mixed input features when interpretability is important. It combines decision trees and is often used for feature selection and interpretability, making it a good option for such cases.
In a relational database, what is used to ensure data integrity across multiple tables?
- Primary Key
- Foreign Key
- Index
- Trigger
A Foreign Key is used in a relational database to ensure data integrity by creating a link between tables. It enforces referential integrity, ensuring that values in one table match values in another. Primary Keys are used to uniquely identify records in a table, not to maintain integrity across tables. Indexes and Triggers serve different purposes.
The _______ is a measure of the relationship between two variables and ranges between -1 and 1.
- P-value
- Correlation coefficient
- Standard error
- Regression
The measure of the relationship between two variables, ranging from -1 (perfect negative correlation) to 1 (perfect positive correlation), is known as the "correlation coefficient." It quantifies the strength and direction of the linear relationship between variables.
How do federated learning approaches differ from traditional machine learning in terms of data handling?
- Federated learning doesn't use data
- Federated learning relies on centralized data storage
- Federated learning trains models on decentralized data
- Traditional machine learning trains models on a single dataset
Federated learning trains machine learning models on decentralized data sources without transferring them to a central server. This approach is privacy-preserving and efficient. In contrast, traditional machine learning typically trains models on a single, centralized dataset, which may raise data privacy concerns.
For graph processing in a distributed environment, Apache Spark provides the _______ library.
- GraphX
- HBase
- Pig
- Storm
Apache Spark provides the "GraphX" library for graph processing in a distributed environment. GraphX is a part of the Spark ecosystem and is used for graph analytics and computation. It's a powerful tool for analyzing graph data.
In computer vision, what process involves converting an image into an array of pixel values?
- Segmentation
- Feature Extraction
- Pre-processing
- Quantization
Pre-processing in computer vision typically includes steps like resizing, filtering, and transforming an image. It's during this phase that an image is converted into an array of pixel values, making it ready for subsequent analysis and feature extraction.
One of the challenges with Gradient Boosting is its sensitivity to _______ parameters, which can affect the model's performance.
- Hyperparameters
- Feature selection
- Model architecture
- Data preprocessing
Gradient Boosting is indeed sensitive to hyperparameters like the learning rate, tree depth, and the number of estimators. These parameters need to be carefully tuned to achieve optimal model performance. Hyperparameter tuning is a critical step in using gradient boosting effectively.
In the context of data warehousing, what does the acronym "OLAP" stand for?
- Online Learning and Prediction
- Online Analytical Processing (OLAP)
- On-Demand Logical Analysis Platform
- Optimized Load and Analysis Process
"OLAP" stands for "Online Analytical Processing." It is a category of data processing that enables interactive and complex analysis of multidimensional data. OLAP databases are designed for querying and reporting, facilitating business intelligence and decision-making.