Comprehensive guide to Algorithms and Data Structures created by me to practice important concepts for technical interviews.

Learning DSA - From 100DaysOfCode challenge to Placement Preparation:) [ C++]

Benchmark a given function for variable input sizes and find out its time complexity

This repo helps keep track about exercises, Jupyter Notebooks and projects from the Data Structures & Algorithms Nanodegree Program offered at Udacity.

Monte Carlo simulation to estimate percolation threshold.

My own Interviewbit solutions

Time and space complexity are terms used in computer science to analyze the efficiency of algorithms. Time Complexity measures the amount of time an algorithm takes to complete as a function of the input size. Space Complexity quantifies the amount of memory space an algorithm uses in relation to the input size.

All about Data Structures and Algorithms.

Algorithmic Software Project for Indian Military Operations to reduce terrorism activities in J&K region.

CL = Command Line. GREP is a command-line utility for searching plain-text data sets for lines that match a regular expression or simply a string

Divide and Conquer technique is used to work out different problems of varyying natures. Our problem at hand is to efficiently search an integer value from grid of size n x n, where n is any integer, using the principles of divide and conquer. The grid has both it's rows as well as columns sorted in ascending order.

This ipynb contains a visualization to the time-complexity analysis - which function grows faster? Why we omit the constants, or why we take the highest degree?

GREP is a command-line utility for searching plain-text data sets for lines that match a regular expression or simply a string. In this, I implemented GREP using Naive Search.

Create a symbol table data type whose keys are two-dimensional points. Use a 2d-tree to support efficient range search and nearest neighbor search.

A library for evaluating the complexity of regular expressions in different languages

Welcome to the 2024 LeetCode Grind 169 Questions Challenge, inspired by the renowned Grind 75 — a dynamic, personalized approach to mastering coding interviews. This challenge is a journey through the top 169 LeetCode questions, handpicked for their value in preparing you for technical interviews.

The course covers basic algorithmic techniques and ideas for computational problems arising frequently in practical applications: sorting and searching, divide and conquer, greedy algorithms, dynamic programming. [2020]

Analysis of Algorithms using C language

This is implementation of customized bio-inspired algorithms for hyperparameter tuning of a custom-ANN, space and time complexity analysis of those bio inspired algos viz. ant-colony (contributed by me), swarm-bee and genetic algo and to compare their accuracies. ANN classifies if patient is prone to heart disease

An aggregator of my completed code challenges in Hacker Rank, containing detailed explanation, benchmarking, time complexity analysis, and thorough testing