Miller-Rabin Primality Test: Probabilistic Prime Testing Explained with Examples
Explore the Miller-Rabin primality test, a fast probabilistic algorithm to check primes. Includes clear examples, visual diagrams, and code snippets.
Extended Euclidean Algorithm: Find Modular Multiplicative Inverse with Examples
Learn the Extended Euclidean Algorithm step by step and discover how it is used to compute the modular multiplicative inverse, with detailed examples, diagrams, and Python code.
Fast Fourier Transform: Efficient Polynomial Multiplication Explained
Explore how the Fast Fourier Transform (FFT) algorithm efficiently multiplies polynomials, including detailed explanations, examples, and insightful mermaid diagrams.
Newton’s Method: Find Square Roots and Function Zeros Efficiently
Explore Newton's Method for finding square roots and zeros of functions with intuitive explanations, examples, and visualizations to master numerical approximation.
Optimization Algorithms: Find Best Solutions with Examples and Visuals
Learn about optimization algorithms, their working principles, and practical examples. Discover how techniques like Gradient Descent, Genetic Algorithms, and Dynamic Programming help in finding the best solutions to complex problems.
Simulated Annealing: Probabilistic Optimization Technique Explained with Examples
Discover Simulated Annealing, a powerful probabilistic optimization technique. Learn its working principle, algorithm, and practical examples with visual explanations.
Genetic Algorithm: Evolutionary Optimization Approach Explained with Examples
Explore the Genetic Algorithm, a powerful evolutionary optimization approach with detailed examples, visualizations, and practical applications.
Particle Swarm Optimization: Swarm Intelligence Algorithm Deep Dive
Explore Particle Swarm Optimization, a powerful swarm intelligence algorithm, with intuitive explanations, examples, and visual insights.
Ant Colony Optimization: Bio-Inspired Path Finding Algorithm Explained
Explore the bio-inspired Ant Colony Optimization algorithm for solving path finding problems with clear examples, visuals, and interactive explanations.
Hill Climbing Algorithm: Local Search Optimization Explained with Examples
Learn the Hill Climbing Algorithm for local search optimization with detailed examples, diagrams, and Python implementation. Understand how it works, its types, advantages, limitations, and applications in AI and optimization problems.
