Joaquin Machulsky's repositories
Algorithms-and-Data-Structures
This repository covers design principles, C++ class implementations and essential concepts for effective algorithmic problem-solving. It includes abstract data types, algorithm analysis, and advanced techniques with practical exercises and projects for real-world application.
Clasificador-Genomas
Proyecto de investigación en ML para identificar factores genéticos en pronóstico de lesiones pre-tumorales. Aprendizaje no supervisado para discernir perfiles genéticos distintivos entre grupos de buen y mal pronóstico, mejorando detección y tratamiento temprano del cáncer.
curso-apis
Introducción a las APIs
Dream-Journal
Project for the subject Data Laboratories, done in Python, using Web Scraping techniques, curation of Data Frames, Data Visualization and Classification, Natural Language Processing and Regression Models.
Goldbachs-Conjecture
This repository contains Haskell functions to explore Goldbach's Conjecture, a classic problem in number theory. Dive into prime numbers, computational verification, and conjecture testing.
Linear-Algebra
Computational Linear Algebra course covering topics like iterative methods, matrix decompositions, and applications. It includes theoretical concepts, practical exercises, and code. Advanced methods like QR factorization, spectral theorem, and iterative solvers for linear systems.
material-analisis-automatico
Machine Learning
Pop-it
Perfect winning strategy to Pop-it nim game with Haskell. This repository provides tools to analyze winning positions, determine optimal moves, and play the game effectively. Dive into functional programming and game theory principles in this educational project.
Programming-Fundamentals
C++ implementations of fundamental algorithms taught on the course. Topics from first order logic and problem specification to time complexity. Algorithms for search and sorting, along with a testing module to verify correctness and efficiency.
Residential-Analysis
Analyzing Argentina's Permanent Household Survey database from INDEC, this project employs C++ to implement solutions. Utilizing first-order logic, problems are precisely defined. Ensuring 100% line coverage on the test suite for thorough evaluation and accuracy.
SOR-Method
This project investigates convergence for solving linear systems. It implements Jacobi and SOR methods, explores convergence, optimizes performance via ω, and analyzes spectral radius/determinant. It aims to enhance iterative method efficiency for linear systems.