📅 2024-04-17 — Session: Implemented and Analyzed Advanced Algorithms in Python
🕒 15:45–16:50
🏷️ Labels: Algorithms, Python, Divide And Conquer, Optimization
📂 Project: Dev
⭐ Priority: MEDIUM
Session Goal:
The session aimed to explore, implement, and analyze various advanced algorithms in Python, focusing on optimization and computational efficiency.
Key Activities:
- Merge-and-Count Algorithm: Explored the inversion counting using a modified Mergesort algorithm, maintaining an O(n log n) time complexity, and implemented it in Python.
- Closest Pair of Points: Implemented a divide-and-conquer algorithm to find the closest pair of points in a 2D space, detailing the steps and functions involved.
- Binary Tree Diameter: Developed a recursive algorithm to calculate the diameter of a binary tree, including a Python implementation.
- Karatsuba Algorithm: Explained and implemented the Karatsuba algorithm for multiplying large numbers using divide-and-conquer, reducing complexity from O(n^2) to O(n^{1.59}).
- Matrix Power Summation: Implemented a strategy to calculate the sum of matrix powers using divide-and-conquer in Python.
Achievements:
- Successfully implemented and tested multiple complex algorithms in Python.
- Gained insights into optimizing algorithms for better computational efficiency.
Pending Tasks:
- Further optimization and testing of the implemented algorithms to ensure robustness and efficiency.
- Explore additional algorithmic strategies for potential improvements.