Practice Memoization And Dynamic Programming (41.2) - Memoization and dynamic programming
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Memoization and Dynamic Programming

Practice - Memoization and Dynamic Programming

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Practice Questions

Test your understanding with targeted questions

Question 1 Easy

Define memoization in your own words.

💡 Hint: Think about how we can save time when calling the same function multiple times.

Question 2 Easy

What is a base case?

💡 Hint: Consider the simplest input for recursive functions.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What is memoization?

A method of sorting data
An optimization technique to store computed values
A recursive function

💡 Hint: Think about how we optimize function calls.

Question 2

Dynamic programming only works for problems that have overlapping subproblems and optimal substructure.

True
False

💡 Hint: Consider the nature of problems suited for optimization.

1 more question available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

Implement both recursive and memoized Fibonacci functions and compare their execution times for n = 30.

💡 Hint: Use time.time() before and after calling the function.

Challenge 2 Hard

Create a dynamic programming solution to solve the coin change problem.

💡 Hint: Construct a table where each index represents the amount and fill in values iteratively.

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Reference links

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