A media company is trying to understand the preferences and viewing habits of their audience. They have a lot of raw data and need insights and visualizations to make strategic decisions. Who would be the most appropriate person to handle this task from the Data Science team?
- Data Scientist
- Data Analyst
- Data Visualizer
- Business Analyst
Data Visualizers are experts in creating insights and visualizations from raw data. They have a deep understanding of data visualization techniques, which is crucial for understanding audience preferences and viewing habits and making strategic decisions based on visualized insights.
The _______ is a component of the Hadoop ecosystem that manages and monitors workloads across a cluster.
- HDFS
- YARN
- Pig
- Hive
The blank should be filled with "YARN." YARN (Yet Another Resource Negotiator) is responsible for resource management and workload monitoring in Hadoop clusters. It plays a crucial role in managing and scheduling jobs across the cluster.
Which Big Data tool is more suitable for real-time data processing?
- Hadoop
- Apache Kafka
- MapReduce
- Apache Hive
Apache Kafka is more suitable for real-time data processing. It is a distributed streaming platform that can handle high-throughput, fault-tolerant, and real-time data streams, making it a popular choice for real-time data processing and analysis.
Which advanced technique in computer vision involves segmenting each pixel of an image into a specific class?
- Object detection
- Semantic segmentation
- Image classification
- Edge detection
Semantic segmentation is an advanced computer vision technique that involves classifying each pixel in an image into a specific class or category. It's used for tasks like identifying object boundaries and segmenting objects within an image.
A company is transitioning from a monolithic system to microservices. They need a database that can ensure strong transactional guarantees. What kind of database system would be suitable?
- NoSQL Database
- NewSQL Database
- Columnar Database
- Time-Series Database
NewSQL databases like Google Spanner are designed to combine the scalability of NoSQL databases with strong transactional guarantees, making them suitable for microservices transitioning from monolithic systems.
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.
You are working on a dataset with income values, and you notice that a majority of incomes are clustered around $50,000, but a few are as high as $1,000,000. What transformation would be best suited to reduce the impact of these high incomes on your analysis?
- Min-Max Scaling
- Log Transformation
- Z-score Standardization
- Removing Outliers
To reduce the impact of extreme values in income data, a log transformation is often used. It compresses the range of values and makes the distribution more symmetrical. Min-Max scaling and z-score standardization don't address the issue of extreme values, and removing outliers may lead to loss of important information.
For translation-invariant tasks in image processing, which type of neural network architecture is most suitable?
- Autoencoders
- Siamese Networks
- Convolutional Neural Networks (CNNs)
- Recurrent Neural Networks (RNNs)
Convolutional Neural Networks (CNNs) are well-suited for translation-invariant tasks, such as image processing, due to their ability to capture local patterns and features. CNNs can automatically learn and detect features in images, making them effective for tasks like object recognition and image classification.
In light of AI ethics, why is the "right to explanation" becoming increasingly important?
- It ensures AI algorithms remain proprietary
- It promotes transparency in AI decision-making
- It limits the use of AI in sensitive applications
- It reduces the complexity of AI algorithms
The "right to explanation" is important as it promotes transparency in AI decision-making. In ethical AI, users should have insight into how AI algorithms arrive at their decisions. This transparency is vital to prevent bias, discrimination, and unethical decision-making, making it a critical aspect of AI ethics.
A common method to combat the vanishing gradient problem in RNNs is to use _______.
- Gradient boosting
- Long Short-Term Memory (LSTM)
- Principal Component Analysis
- K-means clustering
To combat the vanishing gradient problem in RNNs, a common approach is to use Long Short-Term Memory (LSTM) units. LSTMs are designed to alleviate the vanishing gradient issue by allowing gradients to flow over longer sequences.