Questions

1. What is the primary benefit of integrating Java’s concurrency mechanisms into ML workflows?
   1. To increase the programming complexity
   2. To enhance data security
   3. To optimize computational efficiency
   4. To simplify code documentation
2. Which Java tool is highlighted as crucial for processing large datasets in ML projects quickly?
   1. Java Database Connectivity (JDBC)
   2. Java Virtual Machine (JVM)
   3. Parallel Streams
   4. JavaFX
3. What role do custom thread pools play in Java concurrency for ML?
   1. They decrease the performance of ML models.
   2. They are used to manage database transactions only.
   3. They improve scalability and manage large-scale computations.
   4. They simplify the user interface design.
4. Which of the following is a suggested application of Java’s concurrency in ML as discussed in this chapter?
   1. To handle multiple user interfaces simultaneously
   2. To perform data preprocessing and model training more efficiently
   3. To replace Python in scientific computing
   4. To manage client-server architecture...