Object Oriented Programming

GATE

Data Structures

Data Structures in Python

Power BI

Data Science

Django

Data Structure and Algorithm

Python

Recursion

Arrays

Searching

Sorting

String

Linked List

Data Structures in C

Maths

Strings

C++ Tricks

System Design

Theory of Computation

Computer Organization and Architecture

Operating System

Engineering Mathematics

Database

Digital Logic

Computer Networks

GATE 2022

Java

GeeksforGeeks School

Hashing

Competitive Programming

Problem of the Day

School

HTML

Javascript

Bootstrap

Web Development

Android

Microsoft Office

Machine Learning

Resume Builder

Miscellaneous

Gblog

TechTips

React

Advanced JavaScript

DSA Self Paced

CS-subjects

Data Structures and Algorithms

Operating Systems

C Language

DBMS

Basics of CPP

Data Structures ( Basics )

Object Oriented Design

Dynamic Programming

Data Interpretation and Logical Reasoning

Algorithms

Core Java

RESTful APIs

Spring Basics

CPP-Tricks

Basics of Java

Aptitude

GATE YT

Flutter

Application Development

Blockchain

GFG SDE Sheet

SDE Sheet

Deep Learning

Go Programming

Placement

C++ Programs

Data Visualisation

DevOps

Docker

Queue

Matrix

Trie

Stack

Graph

Tree

Magic Numbers

Divide and Conquer

React Native

React JS

Interview-Questions

Advanced Java

cloud-computing

income tax

Artificial Intelligence

Programming Languages

Computer Graphics

Cyber Security

Project Management

DSA / Placements

GATE Prep

Data Analytics / Data Science

Development

Cloud / DevOps

All Courses

Courses

ML & Data Science

Interview Corner

CS Subjects

School Learning

Software and Tools

Tutorials

Google Build with AI

Practice Coding Problems

Connect 1:1 with Experts

Practice

Apply Now!

Post Jobs

Jobs Updates

Jobs

For more details, please go through - <a href="https://www.geeksforgeeks.org/dsa/count-set-bits-in-an-integer/">Count set bits in an integer</a>

Count Set Bits.

For more details, please go through - <a href="https://www.geeksforgeeks.org/dsa/overlapping-subproblems-property-in-dynamic-programming-dp-1/">Overlapping Subproblems Property in Dynamic Programming</a>, <a href="https://www.geeksforgeeks.org/dsa/optimal-substructure-property-in-dynamic-programming-dp-2/">Optimal Substructure Property in Dynamic Programming</a>

Dynamic Programming Tabulation.

For more details, please go through - <a href="https://www.geeksforgeeks.org/dsa/optimal-substructure-property-in-dynamic-programming-dp-2/">Optimal Substructure Property in Dynamic Programming</a>, <a href="https://www.geeksforgeeks.org/dsa/overlapping-subproblems-property-in-dynamic-programming-dp-1/">Overlapping Subproblems Property in Dynamic Programming</a>

Dynamic Programming Memoization.

For more details, please go through - <a href="https://www.geeksforgeeks.org/dsa/longest-consecutive-subsequence/">Longest Consecutive Subsequence</a>

Longest Consecutive Subsequence.

For more details, please go through - <a href="https://www.geeksforgeeks.org/dsa/write-a-c-program-to-print-all-permutations-of-a-given-string/">Permutations of given String</a>

Printing all Permutations.

27th Feb - Min Stack

Merge two Sorted Linked List

To find the count of pairs whose sum is strictly less than a given target, several approaches can be used, such as a naive approach, binary search, or the two-pointer technique. In the naive approach, we generate all possible pairs using two nested loops, but this has a time complexity of O(n^2). A better approach uses binary search after sorting the array, with a time complexity of O(2*nlogn), which significantly reduces the search time. The expected approach, however, is the two-pointer technique, which sorts the array and uses two pointers—one at the beginning and one at the end of the array—to efficiently count pairs in O(nlogn + n) time.
 
The two-pointer technique works by comparing the sum of the elements at the left and right pointers. If the sum is less than the target, all elements between the left and right pointers will form valid pairs with the left element. The count is updated accordingly, and the left pointer is incremented. If the sum is greater than or equal to the target, the right pointer is decremented. This technique provides an optimized solution with a linear time complexity after sorting, making it the most efficient approach for counting pairs with a sum less than a given target.

5th Jan - Count Pairs With Sum Less Than Target

Welcome to the next video of our DSA Course, where we dive into the TREE DATA STRUCTURE.Understand the essential terminologies of Trees like root and leaf nodes, subtrees, and more. We will also dive into N-ary and Binary Trees along with their explanation and applications.Learn how to represent binary trees using structures/classes and arrays, gaining valuable insights into efficient data organization and manipulation.

TREE DATA STRUCTURES | What is Tree? | DSA Course

This video of our DSA Course delves into another crucial data structure - the Queue Data Structure.Discover the working of First In, First Out (FIFO) principle and explore the characteristics that define the Queue data structure. From essential enqueue and dequeue operations to peek(), front(), rear(), isFull(), and isEmpty(), &nbsp;we cover all the Queue Operations!🔍 Gain a comprehensive understanding of different types of Queues, including Input Restricted Queue, Output Restricted Queue, Circular Queue, Double Ended Queue, and Priority Queue. 📊 Learn how we can represent Queues using Arrays and Linked Lists.🌐 Immerse yourself in real-world applications of Queue data structures, illustrated with live examples that showcase their importance in various scenarios. Whether it's managing tasks, processing data, or optimizing system resources, Queues play a crucial role!

WHAT IS QUEUE? | Queue Data Structures | DSA Course

Welcome to our latest video tutorial focusing on finding the K-th smallest element in an unsorted array using the priority queue approach! If you're grappling with algorithms and data structures, particularly in scenarios where efficiency is paramount, this video is tailored for you.In this tutorial, we delve into the priority queue data structure and its application in solving the problem of finding the K-th smallest element in an unsorted array. We'll walk you through the step-by-step process, explaining the underlying concepts and demonstrating how to implement the solution effectively.Join us as we explore the intricacies of priority queues, discuss their properties, and showcase their utility in solving this specific problem. Whether you're preparing for coding interviews or honing your problem-solving skills, understanding this approach will broaden your algorithmic toolkit and empower you to tackle a wide range of challenges.Ready to unravel the mysteries of the priority queue and master the art of finding the K-th smallest element? Watch the video now and embark on a journey to algorithmic excellence! And for detailed explanations and code snippets, don't forget to check out the accompanying article on GeeksforGeeks: <a href="https://www.geeksforgeeks.org/k-largestor-smallest-elements-in-an-array/">https://www.geeksforgeeks.org/k-largestor-smallest-elements-in-an-array/</a>&nbsp;Don't miss out on the opportunity to enhance your algorithmic skills and gain a deeper understanding of priority queues. Like, share, and subscribe for more tutorials and insights into the world of algorithms and data structures. Let's dive into the world of priority queues together. Happy coding!

Kth Largest Element using Priority Queue

Welcome to our Python programming tutorial where we tackle the challenge of finding the frequency of each element in a limited range array in less than O(N) time! Whether you're a Python enthusiast striving for optimization or a coding enthusiast exploring new algorithms, this tutorial is crafted for you.In this tutorial, we delve into the problem of efficiently counting the frequency of each element in a limited range array. We'll guide you through the step-by-step process of solving this problem using Python, providing clear explanations and Python code snippets along the way.Join us as we dissect the problem and explore various techniques and algorithms to achieve frequency counting in less than linear time complexity. From using mathematical formulas to employing clever data structures, we'll cover different strategies to tackle this optimization challenge in Python.Ready to optimize your frequency counting algorithms and achieve efficient solutions? Watch the tutorial now and elevate your proficiency in Python programming! For detailed explanations and code samples, don't forget to check out the accompanying article on GeeksforGeeks: <a href="https://www.geeksforgeeks.org/find-frequency-of-each-element-in-a-limited-range-array-in-less-than-on-time/">https://www.geeksforgeeks.org/find-frequency-of-each-element-in-a-limited-range-array-in-less-than-on-time/</a>Don't miss out on the opportunity to sharpen your algorithmic skills and explore advanced techniques in Python programming. Like, share, and subscribe for more tutorials and insights into algorithm optimization. Let's embark on this coding journey together. Happy coding!

Frequency of Limited Range Array Elements in Data Structures and Algorithms (DSA) | Programming Tutorial

Practice Problems

JavaScript

Linux