Practice Computational Constraints - 30.7.2 | 30. Introduction to Machine Learning and AI | Robotics and Automation - Vol 2
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30.7.2 - Computational Constraints

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Learning

Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What is needed for training deep learning models effectively?

💡 Hint: Think about what kind of hardware processes tasks quickly.

Question 2

Easy

Why is real-time inference critical in robotics?

💡 Hint: Consider what happens if the robot does not respond quickly.

Practice 4 more questions and get performance evaluation

Interactive Quizzes

Engage in quick quizzes to reinforce what you've learned and check your comprehension.

Question 1

What is a primary requirement for training deep learning models?

  • Low computing power
  • High computing power
  • Minimal data

💡 Hint: Think about what hardware is typically used.

Question 2

True or False: Real-time inference is not critical for robotics.

  • True
  • False

💡 Hint: Consider what happens in construction scenarios.

Solve and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

Consider a construction site where a robot must avoid obstacles while laying bricks. Discuss the computational constraints related to data processing and inference for the robot to operate effectively.

💡 Hint: Reflect on both the data volume and the speed of decision-making.

Question 2

Evaluate how cloud computing could address the challenges of high computing power requirements for deep learning model training in civil engineering.

💡 Hint: Think about the benefits of not having to invest heavily in local hardware.

Challenge and get performance evaluation