For real-time object detection in images or videos, the _______ algorithm is widely adopted.
- YOLO (You Only Look Once)
- R-CNN (Region-based Convolutional Neural Network)
- CNN (Convolutional Neural Network)
- HOG (Histogram of Oriented Gradients)
YOLO (You Only Look Once) is a popular algorithm for real-time object detection. It efficiently detects objects in images or videos, making it suitable for various applications, including self-driving cars and surveillance.
What is one major drawback of using the sigmoid activation function in deep networks?
- Prone to vanishing gradient
- Limited to binary classification
- Efficiently handles negative values
- Non-smooth gradient behavior
One major drawback of using the sigmoid activation function in deep networks is its susceptibility to the vanishing gradient problem. This can hinder training deep networks as the gradient becomes very small for extreme values, slowing down learning.
When normalizing a database in SQL, separating data into two tables and creating a new primary and foreign key relationship is part of the _______ normal form.
- First
- Second
- Third
- Fourth
When normalizing a database, creating a new primary and foreign key relationship by separating data into two tables is part of the Second Normal Form (2NF). 2NF eliminates partial dependencies and ensures that every non-key attribute is functionally dependent on the entire primary key. This is an essential step in achieving a fully normalized database.
In complex ETL processes, _________ can be used to ensure data quality and accuracy throughout the pipeline.
- Data modeling
- Data lineage
- Data profiling
- Data visualization
In complex ETL (Extract, Transform, Load) processes, "Data lineage" is crucial for ensuring data quality and accuracy. Data lineage helps track the origin and transformation of data, ensuring that the data remains reliable and traceable throughout the pipeline.
What does the ROC in AUC-ROC stand for?
- Receiver
- Receiver Operating
- Receiver of
- Receiver Characteristics
AUC-ROC stands for Area Under the Receiver Operating Characteristic curve. The ROC curve is a graphical representation of a model's performance, particularly its ability to distinguish between the positive and negative classes. AUC (Area Under the Curve) quantifies the overall performance of the model, with higher AUC values indicating better discrimination.
The process of using only the architecture of a pre-trained model and retraining it entirely with new data is known as _______ in transfer learning.
- Fine-tuning
- Warm-starting
- Model augmentation
- Zero initialization
Fine-tuning in transfer learning involves taking a pre-trained model's architecture and training it with new data, adjusting the model's parameters to suit the specific task. It's a common technique for leveraging pre-trained models for custom tasks.
You are building a movie recommender system, and you want it to suggest movies based on the content or features of the movies. Which type of recommendation approach are you leaning towards?
- Collaborative Filtering
- Content-Based Filtering
- Hybrid Recommendation System
- Popularity-Based Recommendation
In this scenario, you would use a content-based recommendation approach. It recommends items (in this case, movies) based on their content or features, such as genre, actors, and plot. Collaborative filtering and hybrid systems focus on user behavior and preferences, while popularity-based recommendations don't consider movie content.
In a normal distribution, approximately 95% of the data falls within _______ standard deviations of the mean.
- One
- Two
- Three
- Four
In a normal distribution, approximately 95% of the data falls within two standard deviations of the mean. This is a fundamental property of the normal distribution, as specified by the Empirical Rule or the 68-95-99.7 rule, which describes the percentage of data within one, two, and three standard deviations of the mean.
Which of the following databases is best suited for time-series data?
- MongoDB
- PostgreSQL
- Cassandra
- InfluxDB
InfluxDB is specifically designed for time-series data, making it a suitable choice for applications that need to efficiently store and query time-stamped data, such as IoT or monitoring systems. Its structure and optimizations are tailored for this use case.
You're tasked with performing real-time analysis on streaming data. Which programming language or tool would be most suited for this task due to its performance capabilities and extensive libraries?
- Python
- R
- Java
- Apache Spark
For real-time analysis on streaming data, Apache Spark is a powerful tool. It provides excellent performance capabilities and extensive libraries for stream processing, making it suitable for handling and analyzing large volumes of data in real-time.