193 docs tagged with "algorithms"

In this blog post, we'll explore the A* Algorithm, an efficient method for pathfinding and graph traversal.

In this blog post, we'll explore the Activity Selection Problem, a classic greedy algorithm used to select the maximum number of activities that don't overlap.

Adjacency list is used to represent a graph using array and linked list

Advanced concepts related to recursion depth, including dynamic programming and backtracking.

Bloom Filters are probabilistic data structures used in applications where space efficiency is crucial, and approximate answers are acceptable, like database caching and network filtering.

In this post, we'll explore the Ant Colony Optimization (ACO) algorithm, applied to solving the Travelling Salesman Problem (TSP) using a probabilistic and pheromone-based approach.

In this blog post, we'll explore the approaches used in Dynamic Programming (DP), a powerful technique for solving complex problems by breaking them down into simpler subproblems. You'll learn about the two main approaches—Top-Down and Bottom-Up—how they work, their pros and cons, and examples to illustrate their application.

An overview of AVL trees, their properties, and operations.

A B-Tree is a self-balancing tree data structure that maintains sorted data and allows for efficient insertion, deletion, and search operations.

In this blog post, we'll explore the backtracking algorithm, a powerful technique for solving combinatorial problems by building solutions incrementally.

The Balanced Parentheses problem involves determining whether a given string of parentheses is valid, meaning every opening bracket has a corresponding closing bracket in the correct order.

A Balanced Tree is a data structure that maintains a balanced height to ensure efficient operations.

This algorithm checks if the parentheses in a given expression are balanced using a stack to ensure each opening parentheses has a corresponding closing one.

It is a method used to avoid deadlocks in a system by checking if there exists a safe sequence of resource allocation for processes using safety checks based on available resources.

In this blog post, we'll dive into the Bellman-Ford Algorithm, a fundamental graph algorithm used to find the shortest path between nodes in a graph, even with negative weights.

In this blog post, we'll dive into the binary search algorithm, a fundamental technique in computer science for efficiently finding an element in a sorted array.

In this blog post, we'll dive into the binary search algorithm, a fundamental technique in computer science for efficiently finding an element in a sorted array.

In this blog post, we'll dive into the binary search algorithm, a fundamental technique in computer science for efficiently finding an element in a sorted array.

In this blog post, we'll explore binary search in a matrix, an optimized method to find an element in a sorted 2D matrix efficiently in C++.

In this blog post, we'll dive into the rotated array approach with binary search algorithm, a fundamental technique in computer science for efficiently finding an element in a sorted array.

A Binary Search Tree (BST) is a data structure that facilitates efficient searching, insertion, and deletion operations.

A Binary Tree is a data structure in which each node has at most two children.

A bipartite graph is a graph whose vertices can be divided into two disjoint sets such that no two vertices within the same set are adjacent.

A detailed guide on the Bitonic Sort algorithm with Python implementation examples.

In this blog post, we'll explore Breadth-First Search (BFS), a graph traversal algorithm used to explore vertices and edges level by level in a graph.

CatBoost is an efficient gradient boosting algorithm that handles categorical features well, making it a powerful tool for classification and regression problems.

In this blog post, we'll explore how to solve the character replacement problem using the sliding window technique.

This document explores various commonly greedy algorithm patterns, highlighting their definitions, characteristics, and common applications.

This document provides an overview of the Convex Hull problem using the divide-and-conquer approach.

In this post, we'll explore the Decision Tree Algorithm, a popular machine learning model used for classification and regression tasks.

An introduction to Deep Q-Networks, a reinforcement learning technique that combines Q-Learning with deep neural networks to handle complex, high-dimensional state spaces.

Removing a key from a B-tree while maintaining balance

In this blog post, we'll explore Depth-First Search (DFS), a graph traversal algorithm used to explore vertices and edges by going as deep as possible before backtracking.

In this blog post, we'll explore Depth-First Search (DFS) using Java, a graph traversal algorithm used to explore vertices and edges by going as deep as possible before backtracking.

A comprehensive guide covering the time complexity of various operations associated with binary heaps, including rationale and examples.

In this blog post, we'll explore Dijkstra's Algorithm, an efficient method to find the shortest path from a source to all other nodes in a graph.

In this blog post, we'll dive into Dijkstra's Algorithm, a fundamental graph algorithm used to find the shortest path between nodes in a graph.

Explanation and implementation of the Euclidean Algorithm to find the GCD of two numbers.

This post explores Eulerian graphs, their properties, and algorithms for detecting and constructing Eulerian paths and circuits.

In this blog post, we'll explore Exponential Search, a searching algorithm that efficiently finds an element in a sorted array, especially when the size of the array is unknown.

An Expression Tree is a binary tree representing expressions with operators as internal nodes and operands as leaves.

In this post, we’ll explore the Extra Trees Algorithm, an ensemble learning model used for classification and regression tasks, known for its efficiency and randomness in both feature selection and data sampling.

In this blog post, we'll explore the fence painting problem and calculate the number of ways to paint the fence using dynamic programming.

The "Find Indices of Stable Mountains" problem on involves identifying mountains that meet a specific stability criterion 1.

In this blog post, we'll explore the Flood Fill Algorithm, a popular technique used in computer graphics for determining connected regions, such as filling areas in images and solving puzzles like the paint bucket tool in graphics editing software.

In this blog post, we'll dive into the Floyd-Warshall Algorithm, a fundamental graph algorithm used to find the shortest path between all pairs of nodes in a graph.

Floyd’s Cycle Detection Algorithm, also called the Tortoise and Hare Algorithm, is a method used to detect cycles in a linked list. It uses two pointers that move at different speeds through the list to determine if a cycle exists.

In this blog post, we'll explore the Floyd's-Algorithm, an efficient method to implement all pair shortest paths

In this blog post, we'll explore the Fractional Knapsack problem, a greedy algorithm-based approach to maximize the value of items within a weight limit by taking fractions of items.

In this post, we'll explore the Fractional Knapsack Problem, a greedy algorithm used to maximize the value of items that can be fit into a knapsack with a weight limit.

In this blog post, we'll explore the Fractional Knapsack Problem, a greedy algorithm used to maximize the value of items that can be carried in a knapsack with a weight limit.

is a mathematical framework used to study decision-making in situations where multiple players interact.

is a mathematical framework used to study decision-making in situations where multiple players interact.

This post explores generating the Fibonacci sequence using recursion. We'll delve into the recursive approach and provide code implementations in multiple languages, including C++, Java, Python, JavaScript, and Go.

In this blog post, we'll explore Graph Coloring, Graph coloring refers to the problem of coloring vertices of a graph in such a way that no two adjacent vertices have the same color.

In this document, we explore the graph coloring problem and provide a C implementation using a greedy algorithm.

The program is to return a deep copy of the graph, preserving the structure and values of its nodes.

Reverse a directed graph so that the incoming edges will be converted to outgoing edges betwwen the same nodes.

Greatest Common Divisor (GCD) and Least Common Multiple (LCM) are fundamental algorithms for divisibility.

Hashing is a technique used to uniquely identify a specific object from a group of similar objects. It involves mapping large data to fixed-size values.

A detailed guide on the Heap Sort algorithm with C++ implementation examples.

The Heap Tree is a specialized binary tree used for efficient priority queue operations and sorting.

In this blog post, we'll explore the Hopcroft-Karp algorithm, an efficient method for finding the maximum matching in a bipartite graph.

In this blog post, we'll explore Huffman Coding, a popular lossless data compression algorithm that assigns variable-length codes to input characters based on their frequencies.

In this blog post, we'll explore how to identify problems that can be effectively solved using Dynamic Programming (DP) techniques, focusing on the key properties of optimal substructure and overlapping subproblems.

Data Structures and Algorithms are the building blocks of computer science. They are essential for writing efficient code and solving complex problems.

Hashing is an essential technique in data structures and algorithms used to optimize data retrieval, storage, and management through efficient key-value mapping.

Mathematical algorithms are essential for solving various computational problems and are widely used in both theoretical computer science and practical applications. They underpin many algorithms used in competitive programming and other fields.

Memoization is an essentail part for optimization technique used to improve the efficiency of recursive algorithms by storing previously computed results.

The Two Pointers technique is an efficient algorithmic strategy used to solve various problems involving arrays or lists by utilizing two indices.

In this post, we'll explore the Independent Component Analysis (ICA) Algorithm, a powerful technique in statistical data analysis.

Inserting a key into a B-tree while maintaining its properties.

A B-tree is a self-balancing tree data structure that maintains sorted data for efficient insertion, deletion, and search operations.

A B-tree is a self-balancing tree data structure that maintains sorted data for efficient insertion, deletion, and search operations.

In this blog post, we'll explore the iterative binary search algorithm, a fundamental technique in computer science for efficiently finding an element in a sorted array. You'll learn what iterative binary search is, how it works, and its time complexity. We'll also cover practical applications and common problems you can solve using this algorithm. By the end, you'll have a thorough understanding of iterative binary search and how to implement it in your programming projects.

The problem aims to maximize total profit by scheduling a set of jobs, each with a deadline and profit, ensuring selected jobs are completed within their deadlines.

In this blog post, we'll explore the Job Sequencing problem, a classical greedy algorithm that schedules jobs within their deadlines to maximize profit.

In this blog post, we'll explore Johnson's Algorithm, a method to find the shortest paths between all pairs of nodes in a graph, even with negative weights.

This post explores the use of Jump Search Algorithm. We'll provide code implementations C++.

A K-D Tree is a space-partitioning data structure for organizing points in a k-dimensional space.

In this post, we'll explore the k-Nearest Neighbors (k-NN) Algorithm, one of the simplest and most intuitive algorithms in machine learning.

In this blog post, we'll explore Kadane's Algorithm, a dynamic programming algorithm used to find the Maximum Sum Subarray in an array.

In this blog post, we will delve into Kahn's Algorithm, an efficient method for topological sorting of a directed acyclic graph (DAG). This algorithm provides a way to find a linear ordering of vertices such that for every directed edge u → v, vertex u comes before vertex v.

A comprehensive guide to the Knuth-Morris-Pratt (KMP) string matching algorithm, including theory, analysis, and implementations in multiple languages

In this blog post, we'll explore Kosaraju's Algorithm, an efficient algorithm used to find all Strongly Connected Components (SCCs) in a directed graph.

In this blog post, we'll explore Kruskal's Algorithm, a greedy algorithm used to find the Minimum Spanning Tree in a graph.

Learn about Kruskal's algorithm, a minimum spanning tree algorithm that works by sorting the edges and adding them one by one if they don't form a cycle.

The Least Recently Used (LRU) algorithm is a cache replacement policy that evicts the least recently used items first.

An overview of Least Recently Used Scheduling and its applications in programming.

In this post, we'll explore the Linear Regression Algorithm, one of the most basic and commonly used algorithms in machine learning.

In this post, we'll explore the Logistic Regression Algorithm, a widely used classification model in machine learning.

Calculating the longest path from a given source in a Directed Acyclic Graph (DAG) with weighted edges.

In this blog post, we will explore an efficient solution to the Longest Repeating Character Replacement problem using sliding window and frequency count.

In this blog post, we will explore how to find the longest substring containing exactly K distinct characters using the sliding window technique.

This document explains the 'Longest Substring Without Repeating Characters' problem, including its description, approach, and implementation.

In this blog post, we'll explore how to find the maximum sum of any subarray of size K using the Sliding Window Algorithm.

Maximum minimum finding using divide and conquer approach to reduce the number of comparisions.

This document explains the Merge Intervals problem, including its description, approach, and implementation.

This problem is a common exercise in understanding array manipulation and is often used to illustrate the two-pointer technique

A MinStack is a data structure that supports standard stack operations while efficiently retrieving the minimum element in constant time.

In this blog post, we'll explore how to solve the problem of minimizing the maximum value between two arrays using binary search and mathematical reasoning.

In this blog post, we'll explore Minimum Spanning Tree (MST) algorithms, specifically Prim's and Kruskal's algorithms, which are used to find the minimum cost spanning tree in a weighted graph.

Modular arithmetic is a fundamental concept in mathematics, essential for cryptography and number theory.

Modular Exponentiation is an algorithm used to efficiently compute large powers modulo a number, using a technique called exponentiation by squaring.

Monotonic Stack is a data structure technique used to maintain elements in a particular order, typically increasing or decreasing, and is commonly used for solving problems involving range queries, such as finding the next greater element.

Monotonic Stack is a data structure technique used to maintain elements in a particular order, typically increasing or decreasing, and is commonly used for solving problems involving range queries, such as finding the next greater element.

An overview of the Multilevel Queue Scheduling Algorithm and its applications in programming.

An overview of mutual recursion and its applications in programming.

Overview and implementation of the N-Queens problem using a backtracking algorithm.

The N-Queens problem is a classic backtracking problem where the objective is to place N queens on an N×N chessboard such that no two queens threaten each other.

The N-Queens Problem is a classic problem where the objective is to place `N` queens on an `N x N` chessboard such that no two queens can attack each other. A queen can attack any other piece in the same row, column, or diagonal, making it challenging to place all `N` queens without conflict.

In this post, we’ll explore the Naive Bayes Theorem, a fundamental probabilistic algorithm used for classification tasks based on Bayes' Theorem and the assumption of conditional independence.

Simple method to find all occurrences of a pattern within a text by comparing each character.

An overview of Non-Tail Recursion and its applications in programming.

This document explains the Odd Even Linked List problem, including its description, approach, and implementation.

Solving the 0/1 Knapsack problem to optimize the packing of supplies for disaster relief missions.

In this blog post, we'll explore the PageRank algorithm, a method used to rank web pages based on their link structure.

Solve the Painter Partition problem using Binary Search and Greedy approaches.

This document explains the Palindrome Linked List problem, including its description, approach, and implementation.

Overview and examples of Parity Partition Sort.

The "Plus One" dsa problem is a classic algorithm challenge that involves manipulating an array of digits. The goal is to add one to a number represented by an array of its digits.

An introduction to policy gradient methods in reinforcement learning, including their role in optimizing policies directly for better performance in continuous action spaces.

Addition of two polynomials represented as linked lists and displays the resulting polynomial

Practice problems for Greedy Algorithms, categorized by difficulty and topic. These problems help in understanding the practical application of greedy strategies in solving algorithmic challenges.

Here are some practice problems for the Two Pointers technique, including an implementation to find the maximum distance between two elements with a specific condition.

Here are some practice problems for the Two Pointers technique, divided into topic-wise and difficulty-wise categories.

Practice problems for Binary Search Tree (BST), categorized by difficulty and topic. These problems help in understanding the structure and operations of BSTs.

Here are some practice problems for Binary Search, divided into topic-wise and difficulty-wise categories.

1. Easy Level

1. Easy Level

Here are some practice problems for heaps, divided into topic-wise and difficulty-wise categories.

1. Basic Operations on Linked List

Here are some practice problems for the Sliding Window technique, divided into topic-wise and difficulty-wise categories.

Basic Stack Operations:

Here are some practice problems for strings

1. Easy Level

Here are some practice problems for tries

A comprehensive list of practice problems focused on combinatorics, covering various topics and concepts.

In this post, we'll provide a list of curated practice problems on Binary Trees from platforms like LeetCode and GeeksforGeeks. Binary Trees are fundamental in computer science, and practicing these problems will help in strengthening your understanding of tree data structures.

In this post, we'll provide a list of curated practice problems on Trees from platforms like LeetCode and GeeksforGeeks. Trees are fundamental data structures in computer science, and practicing these problems will help strengthen your understanding of tree concepts and algorithms.

In this blog post, we'll explore Prim's Algorithm, a greedy algorithm used to find the Minimum Spanning Tree in a graph.

Explore Prim's algorithm, a minimum spanning tree algorithm that starts with a single vertex and expands the MST one edge at a time.

In this blog post, we'll explore Prim's Algorithm, a greedy algorithm used to find the Minimum Spanning Tree (MST) of a weighted undirected graph.

In this post, we’ll explore Principal Component Analysis, a fundamental technique in unsupervised learning used for dimensionality reduction and data visualization.

An overview of Priority Scheduling and its applications in programming.

An overview of the Q-Learning Algorithm, a model-free reinforcement learning method that learns the optimal action-value function to guide decision-making.

Basic Queue Problems:

In this post, we’ll dive into the Random Forest Algorithm, an ensemble learning model used for classification and regression tasks, known for its robustness and versatility.

Randomized quicksort is a sorting algorithm that is an extension of quicksort, but with a random pivot selection

Recursion is a programming technique where a function calls itself directly or indirectly in order to solve a larger problem by breaking it down into smaller, more manageable sub-problems. It is commonly used in algorithms involving divide and conquer strategies, tree traversal, and dynamic programming.

An overview of recursion depth and its role in recursive algorithms.

In this blog post, we'll explore the recursive binary search algorithm, a fundamental technique in computer science for efficiently finding an element in a sorted array. You'll learn what recursive binary search is, how it works, and its time complexity. We'll also cover practical applications and common problems you can solve using this algorithm. By the end, you'll have a thorough understanding of recursive binary search and how to implement it in your programming projects.

In this post, we’ll explore the concept of regression in supervised learning, a fundamental approach used for predicting continuous outcomes based on input features.

This document explains the Removing Stars From a String problem, including its description, approach, and implementation.

This document explains the Reverse Linked List problem, including its description, approach, and implementation.

Definition:

A structured roadmap to guide you through mastering Data Structures and Algorithms.

Learn about Shell Sort, an in-place comparison-based sorting algorithm that generalizes insertion sort to allow the exchange of items that are far apart.

The Sieve of Eratosthenes is an efficient algorithm to find all prime numbers up to a given limit.

In this blog post, we'll explore the Sliding Window Algorithm, an efficient technique for solving problems related to arrays or strings.

A stack permutation is a reordering of an input sequence that can be achieved using a single stack with push and pop operations.

Reversing a stack involves changing the order of elements so that the bottom becomes the top and vice versa.

The Stock Span Problem is a financial problem that calculates the span of stock's price on a given day.

A detailed guide on the Stooge Sort algorithm with Python implementation examples.

An overview of the Strand Sort Algorithm and its applications in programming.

Strassen's matrix multiplication is an efficient algorithm that reduces the time complexity of multiplying two matrices.

Basics of String Data Structure

Operations in String

This program reverses a given string by pushing its characters onto a stack and then popping them back into the string.

A Sum Tree is a binary tree where each node's value is equal to the sum of the values of its left and right children, with the property holding true for all nodes in the tree.

In this post, we’ll explore the concept of supervised learning, a fundamental approach in machine learning where models are trained using labeled data.

SVM is a powerful machine learning model known for its effectiveness in classification tasks and its ability to handle high-dimensional data.

A comprehensive guide to understanding and implementing the sweep line algorithm for computational geometry.

This document explains the Merge Intervals problem using the Sweep Line Algorithm, including its description, approach, and implementation in C++.

An overview of t-SNE, a popular technique for visualizing high-dimensional data in two or three dimensions.

Explore the world of Data Structures and Algorithms (DSA) with Algo's comprehensive learning resources. From fundamental concepts to advanced topics, Algo provides a structured pathway to help you master DSA and enhance your programming skills.

An overview of Tail Recursion and its applications in programming.

In this post, we'll explore a solution to the Trapped Rainwater problem, calculating how much rainwater can be held within a terrain represented by an elevation map using a dynamic programming approach.

An in-depth guide to tree data structures, covering types of trees, traversal methods, balancing, and algorithms with implementations.

An overview of Tree Recursion and its applications in programming.

In this blog post, we'll explore the Two Pointers Algorithm, an efficient technique for solving problems related to arrays or strings.

This document explains the Two Sum problem, including its description, approach, and implementation.

Explore the different types of data structures and algorithms that form the foundation of problem-solving in computer science.

In this post, we’ll explore the concept of unsupervised learning, a fundamental approach in machine learning where models are trained using unlabeled data.

Unwinding in recursion is the phase where recursive calls return back up the call stack, resolving each call step by step in reverse order

In this blog post, we'll explore the Warshall's-Algorithm, an efficient method to Compute the transitive closure of a given directed graph

Algo is your gateway to mastering Data Structures and Algorithms (DSA). Whether you're a coding enthusiast, a student, or a professional looking to enhance your programming skills, Algo is here to guide you through the intricate world of DSA.

A HashSet is a data structure used to store unique elements and provides efficient insertion, deletion, and search operations.

Data Structures and Algorithms (DSA) form the backbone of computer science and programming. Learn what DSA is, why it's important, and how it can enhance your coding skills.

Hashing is a technique used to uniquely identify a specific object from a group of similar objects. Hash maps are data structures that implement this technique.

Mathematical Algorithms play a crucial role in solving complex problems efficiently in both DSA and competitive programming.

Memoization is an optimization technique used primarily to speed up recursive algorithms by caching previously computed results.

XGBoost is a highly efficient and scalable machine learning algorithm known for its accuracy and speed in solving both classification and regression problems.