Practice Gradient Descent - 6.4.1 | 6. Optimization Techniques | Numerical Techniques
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Gradient Descent

6.4.1 - Gradient Descent

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Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What is the primary goal of Gradient Descent?

💡 Hint: Think about what we aim to solve in optimization.

Question 2 Easy

What does the learning rate determine in Gradient Descent?

💡 Hint: How quickly do you want to move toward the solution?

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What does Gradient Descent aim to optimize?

Maximize a function
Minimize a function
Both

💡 Hint: Think about the general goal of optimization.

Question 2

True or False: The learning rate must always be 1 for Gradient Descent.

True
False

💡 Hint: Does it have to be a specific number?

2 more questions available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

Given a quadratic function, derive the first few steps using Gradient Descent, assuming a learning rate of 0.1.

💡 Hint: Use the derivative to determine the gradient, then apply the update formula.

Challenge 2 Hard

Discuss a scenario in which Stochastic Gradient Descent may provide better results than Batch Gradient Descent.

💡 Hint: What might happen if we never adjust based on individual data points?

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