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

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.

Grind 75 is a dynamic list of top LeetCode interview questions created in 2023. It's up-to-date and well-chosen. We can personalize it according to our schedule, time constraints, and preferences.

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]

This repository documents my systematic revision of Data Structures & Algorithms

The distance between two documents to be the angle between their word frequency vectors. The document distance problem is thus the problem of computing the distance between two given text documents.

Big O Playground is an interactive software platform for learning, analyzing, visualizing, and comparing algorithmic complexity through live code execution, runtime instrumentation, and educational visual feedback.

Sentiment Analysis & Monte Carlo Tree Search with Nested Rollout Policy Adaptation for Business

⏱ TIME COMPLEXITY ANALYSIS ⏱ Use Python to analyze and answer questions about the texts and calls contained in the dataset. Then, perform run time analysis of the solution and determine its efficiency ⏱

Efficiency test of different algorithms used to simulate the spread of a wildfire.

CSCI570 Analysis of Algorithms Project: Sequence Alignment Problem

Numerical investigation into the distributional analysis of the time complexity of Euclid's algorithm. Sheds numerical light on an "obscure" constant related to a certain variance.

A lightweight Python package implementing common searching and sorting algorithms. Provides clean, reusable functions along with optional execution time analysis. Ideal for learning algorithms, performance comparison, and practical use in projects.

Implementation of InsertionSort and MergeSort and valutation of time complexity

Comparison of time complexities between different Sort (Bubble and Merge) and Search (Linear and Binary) algorithms

Implementazione BinaryTree e RedBlackTree, valutandone la complettà temporale in caso di inserimento e ricerca

Bidirectional traveling salesman problem using branch and bound depth-first search and stochastic local search followed by a time complexity analysis.

Implementazione degli algoritmi per il calcolo del Minimum Spanning Tree: Kruskal e Prim, e valutazione delle diverse applicazioni dei due algoritmi nei diversi casi di applicazione (matrice adiacenza sparsa o densa)