Practice Approaches To Dynamic Programming (7.4) - Understand the Principles of Dynamic Programming for Algorithmic Optimization
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Approaches to Dynamic Programming

Practice - Approaches to Dynamic Programming

Learning

Practice Questions

Test your understanding with targeted questions

Question 1 Easy

Define memoization in your own words.

💡 Hint: Think about caching results in an array or dictionary.

Question 2 Easy

What is the primary difference between the top-down and bottom-up approaches?

💡 Hint: Consider how you would walk up a staircase versus building it from the ground up.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What is memoization?

Storing all results
Using sweeping predictions
Caching results of expensive calls

💡 Hint: Think about how you can save a result to reuse later.

Question 2

Is the bottom-up approach generally faster than the top-down approach with memoization?

True
False

💡 Hint: Consider what happens each time a recursive call is made versus a simple loop.

1 more question available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

Implement a function using the top-down approach to solve the 0/1 knapsack problem, where you select items based on their weights and values to maximize the total value within a given weight limit.

💡 Hint: Think about the choices you have for each item: include it or exclude it.

Challenge 2 Hard

Create an iterative solution for the Longest Common Subsequence (LCS) problem using the bottom-up approach.

💡 Hint: Remember to consider character matches and the results from previous calculations.

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Reference links

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