Dynamic Programming and Backtracking Full Course 2023 | Ace Coding Interviews With Ease | Scaler

🔹Introduction to Dynamic Programming:

Dynamic Programming is most commonly an optimization over plain recursion. A recursive solution that has repeated calls for the same inputs is optimized using Dynamic Programming. In a nutshell, the results of subproblems are stored, to omit the need of re-computing them when required. This simple optimization reduces time complexities from exponential to polynomial.

🔹Applications of Dynamic Programming:

Dynamic programming is used where we have problems, which can be divided into similar sub-problems so that their results can be re-used. From this exclusive dynamic programming tutorial, you can learn how to solve important coding problems.

🔹 What is Backtracking Algorithm in Data Structures and Algorithm?

Backtracking consists of building a set of solutions in an incremental manner. All the solutions that fail to satisfy the constraints will be removed. The algorithm builds a solution step by step increasing levels over time. Usually, we use a backtracking algorithm for to find solutions to decision problems as well as optimization problems. Sometimes, backtracking is also used for enumeration problems.

Backtracking algorithm is not just useful for coding interviews but also for competitive programming. We have even covered important questions like N queens problem using backtracking to help you gain more insights into data structures and algorithms.

The following topics are covered in this video 👇🏼

0:00 - Introduction
3:11 - Longest Increasing Sub-sequence Problem
15:13 - Regular Expression Match Problem
45:13 - Max Sum Path in Binary Tree

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