Notebooks used during the development of a project converting an oral request of travel through cities into a travel plan using Natural Language Processing to parse the request, extract and order the locations based on the syntax of the request.

This repository explores two optimization algorithms: the Traveling Salesman Problem (TSP) and Nearest Neighbor Search (NNS). It features Jupyter notebooks implementing brute-force solutions to both problems, utilizing Euclidean distance calculations and path visualizations. Ideal for learning about algorithm efficiency and optimization techniques.

The Maze-Navigation-Problem repository contains a Jupyter Notebook detailing strategies for solving maze navigation problems using algorithms. This project demonstrates the application of search techniques in artificial intelligence to find paths through complex mazes, making it an educational tool for students and researchers interested in AI.