Ian Carlo Carmona Serrano's Projects
This repository includes an implementation of a genetic algorithm specifically designed to solve Sudokus. Explore this implementation and discover how genetic algorithms can effectively address this challenge.
The course "Natural Language Processing Applications" in the Artificial Intelligence program at the National Polytechnic Institute (IPN).
Flores amarillas
This repository contains the exercises I completed in the course of Artificial Intelligence Fundamentals. It covers topics such as agents, min and max, depth and breadth-first search, KNN, K-means, decision trees, and Prolog statements.
This repository contains practices of Bioinspired Algorithms, highlighting optimization algorithms such as PSO and genetic algorithms. Explore implementations and applications in optimization problems among others
This repository contains the exercises carried out in the Digital Image Processing course. Some topics related to the exercises include RGB manipulation, histogram editing, image compression, image understanding, image encoding and decoding, image classification, noise, and JPEG format.
This repository contains the project for the Web course, which consists of a CRUD in Node.js. It includes technologies such as JavaScript, HTML, CSS with Bootstrap, and Just Validation.
This is my repository of my GifExpertApp
This program is a project carried out in the Natural Language Processing course, which is a Taylor Swift song recommender. It utilizes topics such as sentiment analysis in texts, text vectorization, and the removal of stopwords.
This project contains the work completed for the Analysis and Design of Systems course, which includes a complete daycare system along with its respective design and analysis documentation.
This repository contains all the exercises done in the Theory of Computation course, addressing topics such as deterministic and nondeterministic finite automata, as well as grammar generation, along with an implementation of the Turing machine.
This repository contains the exercises from the course on computer vision, which includes topics such as image classification, object detection, introduction to perceptron, and classification algorithms like KNN and K-means.