Скачать или смотреть LeetCode 53: Maximum Subarray | Python Solution | Kadane's Algorithm

🔍 Solve the classic maximum subarray problem using #kadanealgorithm in #python. Learn how to find the contiguous subarray with the largest sum in a given array of integers. #dynamicprogramming #arrays

⏱️ **Time Complexity**: O(n)
🧮 **Space Complexity**: O(1)

Timestamps
00:01 - Understanding problem statement
00:43 - Brute force approach
02:43 - Big O Notation explained
03:20 - Using Kadane's algorithm
05:43 - Kadane's Algorithm - dry run
08:02 - Big O Notation calculated
08:35 - Python code walk-through
09:23 - Solution analysis - runtime + memory
09:31 - Conclusion

Key Concepts
Kadane's Algorithm
Dynamic Programming
Array Traversal
Maximum Sum Calculation
Local vs Global Maximum

Learning Points
Understanding how to track running sums efficiently
Implementing the optimal O(n) solution with constant space
Handling negative numbers in arrays
Recognizing when to reset cumulative sums

Related Problems
LeetCode 121: Best Time to Buy and Sell Stock
LeetCode 152: Maximum Product Subarray
LeetCode 918: Maximum Sum Circular Subarray
LeetCode 1567: Maximum Length of Subarray With Positive Product

Target Audience
This video is perfect for software engineers preparing for coding interviews, computer science students learning algorithm fundamentals, and anyone looking to improve their problem-solving skills with arrays and dynamic programming.

Prerequisites
Basic understanding of arrays in Python
Familiarity with loops and conditional statements
Elementary knowledge of time and space complexity analysis

Useful Links
📝 Problem: https://leetcode.com/problems/maximum...
💻 Solution Code: https://leetcode.com/problems/maximum...

Additional Tips
Pay attention to how we handle the case when all numbers are negative
Notice the elegance of Kadane's algorithm in tracking both current and maximum sum
Observe how we avoid nested loops to achieve linear time complexity

Call to Action
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