Selected MCQ

Current Question
What distinguishes 'batch' training from 'online' training?
  • A. Batch uses all data at once per update; online uses one sample at a time
  • B. Batch normalizes data; online does not
  • C. Online uses GPU; batch uses CPU
  • D. Batch increases learning rate automatically
Correct Answer: A
Explanation:
Batch training updates using the entire dataset per iteration; online (stochastic) updates per sample.
Related Question 1
What distinguishes 5G from previous cellular generations?
  • A. Lower latency and higher bandwidth
  • B. Use of copper lines
  • C. No need for antennas
  • D. Shorter battery life
Correct Answer: A
Explanation:
5G provides much higher speeds and significantly lower latency compared to 4G.
Related Question 2
Which term describes training a model on multiple GPUs or servers simultaneously?
  • A. Distributed training
  • B. Batch processing
  • C. Layer-wise training
  • D. Fusion
Correct Answer: A
Explanation:
Distributed training spreads the training process across multiple devices or machines.
Related Question 3
What is the purpose of a 'validation set' during model training?
  • A. To train the model parameters
  • B. To evaluate the final model performance
  • C. To tune hyperparameters and avoid overfitting
  • D. To serve as training data
Correct Answer: C
Explanation:
The validation set is used to tune hyperparameters and detect overfitting during training.
Related Question 4
In terms of robot classification, what distinguishes an industrial robot?
  • A. Operated remotely via telepresence
  • B. Designed specifically for factory automation tasks
  • C. Uses only biological components
  • D. Lack of any sensors
Correct Answer: B
Explanation:
Industrial robots are designed for tasks such as assembly and welding in manufacturing environments.
Related Question 5
What is the primary advantage of using a GPU over a CPU for training deep neural networks?
  • A. Faster single-thread performance
  • B. Large memory capacity
  • C. Parallel processing of many operations
  • D. Built-in neural network instructions
Correct Answer: C
Explanation:
GPUs can perform many operations in parallel, greatly speeding up matrix computations in neural network training.