Algorithms & Data Structure

date
Dec 9, 2024
type
Post
AI summary
slug
algorithm
status
Published
tags
Algorithm
summary
This blog post provides an overview of key concepts in algorithms, starting with Dynamic Programming and Greedy Algorithms, exploring techniques like Divide and Conquer, Fourier Transform, and foundational theory on P and NP, NP-Completeness, and NP-Hard problems. It delves into Linear Programming and Integer Linear Programming, focusing on Approximation Algorithms and their applications, including TSP (Traveling Salesman Problem) approximation schemes. The post also covers advanced topics such as RSA Public Key Cryptography and the Basics of Quantum Computing, along with an introduction to advanced data structures, offering a comprehensive guide to important algorithmic techniques and their real-world applications.
 

Dynamic Programming, Greedy Algorithms

  1. Divide and Conquer
  1. Fourier Transform
  1. Dynamic Programming
  1. Greedy Algorithms
  1. P and NP, NP-Completeness, NP-Hard
 

Approximation Algorithms and Linear Programming

  1. Linear Programming
  1. Integer Linear Programming
  1. Approximation Algorithms
  1. TSP and Approximation Schemes
 

Advanced Data Structures, RSA and Quantum Algorithms

  1. RSA Public Key Cryptography
  1. Basics of Quantum Computing
 
 

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