Practice Optimization Methods (2) - Optimization Methods - Advance Machine Learning
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Optimization Methods

Practice - Optimization Methods

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Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What is an objective function?

💡 Hint: Think of it as a measure of model performance.

Question 2 Easy

Name one loss function used in regression tasks.

💡 Hint: What do we measure in regression?

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What is an objective function?

A function to maximize only
A function to minimize only
A function to either minimize or maximize

💡 Hint: Think about its role in optimization.

Question 2

True or False: Gradient Descent guarantees a global minimum in all cases.

True
False

💡 Hint: Consider the types of functions.

2 more questions available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

An algorithm suffers from overfitting. How would you apply L1 or L2 regularization to mitigate this issue? Provide a practical coding example.

💡 Hint: Think about how regularization interacts with coefficients.

Challenge 2 Hard

You are tasked with optimizing a neural network with high variance in results. Discuss which hyperparameter tuning techniques could you implement and justify your choices.

💡 Hint: Consider how much time you can allocate for tuning.

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Reference links

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