Leetcode
🎥 In this comprehensive video lecture on solving LeetCode Problem 347, we delve into various strategies for efficiently finding the top k frequent elements in a given array.
👨🏻💻 Code Link:
https://github.com/mohanmanis/Lecture...
🖇️ Heap Code Link: https://github.com/mohanmanis/Lecture...
👨🏻💻 problem link:
https://leetcode.com/problems/top-k-f...
🔍 The lecture begins by elucidating the brute force sorting method, followed by an exploration of more optimized techniques.
⚙️ Firstly, we explore the utilization of Min Heap and Max Heap data structures, highlighting their advantages over the brute force method. A detailed comparison between Max Heap and Min Heap time complexities is provided, shedding light on their respective strengths and weaknesses.
🔄 Subsequently, we unveil the optimal solution of employing bucket sort to tackle the top-k-frequent-elements problem. This approach optimally leverages the inherent characteristics of bucket sorting, leading to enhanced performance and efficiency.
💻 To complement the theoretical explanations, code implementations in JavaScript are provided for each approach discussed in the lecture, including Max Heap, Min Heap, and Bucket Sort solutions, enabling viewers to grasp the practical implementation details.
🔗 For a deeper understanding of the concepts discussed and to access the code implementations, please refer to the code available at https://github.com/mohanmanis/Lecture...
and the problem statement at https://leetcode.com/problems/top-k-f...
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