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mat281

Clases MAT281 - Segundo Semestre (UTSFM)

https://github.com/fralfaro/mat281

Science Score: 67.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ✓
    CITATION.cff file
    Found CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
  • ✓
    DOI references
    Found 2 DOI reference(s) in README
  • ✓
    Academic publication links
    Links to: zenodo.org
  • ○
    Academic email domains
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    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (8.4%) to scientific vocabulary
Last synced: 10 months ago · JSON representation ·

Repository

Clases MAT281 - Segundo Semestre (UTSFM)

Basic Info
  • Host: GitHub
  • Owner: fralfaro
  • License: mit
  • Language: Python
  • Default Branch: main
  • Homepage: http://falfaro.xyz/MAT281/
  • Size: 57.4 MB
Statistics
  • Stars: 41
  • Watchers: 1
  • Forks: 0
  • Open Issues: 2
  • Releases: 1
Created over 1 year ago · Last pushed 10 months ago
Metadata Files
Readme Changelog Contributing License Code of conduct Citation

README.md

MAT281 - Matemticas Aplicadas

example workflow pre-commit Pytest Link a la Documentacin Link a la Documentacin Link a la Documentacin

Link a la Documentacin Open in Dev Containers DOI

Objetivo de la Asignatura

Este curso proporciona las habilidades esenciales para desempearse como Data Scientist utilizando Python. Se abordarn desde la manipulacin de datos hasta la implementacin de modelos de Machine Learning, con un enfoque prctico y aplicado.

Para obtener una visin general y detallada del curso, consulta la siguiente presentacin: link

Requisitos de entrada

  • Clculo y lgebra Principios fundamentales.
  • Probabilidad y Estadstica Conceptos bsicos.
  • Optimizacin Mtodos esenciales.
  • Python Familiaridad con su sintaxis y estructuras bsicas.

Contenidos temticos

  • Toolkit Bsico Herramientas esenciales para anlisis de datos.
  • Manipulacin de Datos Tcnicas eficientes con Pandas y NumPy.
  • Visualizacin Creacin de grficos con Matplotlib y Seaborn.
  • Machine Learning Introduccin a algoritmos clave con Scikit-Learn.

Recursos de Aprendizaje

Textos Gua Principales:

  • Python Data Science Handbook Jake VanderPlas Un manual completo sobre Python para ciencia de datos, cubriendo NumPy, Pandas, Matplotlib y Scikit-Learn.

Lecturas Complementarias:

  • Hands-On Machine Learning Aurlien Gron
  • Data Science from Scratch Joel Grus
  • Python for Data Analysis Wes McKinney

Repositorios de GitHub:

Evaluacin

Tipo | Frecuencia | Modalidad | Entrega | Penalizacin| |---------------------|------------|------------|------------------|--------------------------| | Laboratorios | Semanal | Individual | Final de clases | nota 0 | | Tareas | Mensual | Individual | T1: 26-09-2025
T2: 14-11-2025 | -25 puntos | | Proyecto | Semestral | Grupal | 28-11-2025 | -25 puntos |

Nota Final: La nota final ser el promedio ponderado entre los laboratorios, tareas y el proyecto final del curso.

$$ Nf = 0.3\bar{nl} + 0.35\bar{nt} + 0.35np $$

Importante!: Todos los entregables se deben subir al repositorio personal del estudiante (en GitHub). Las notas se trataran de actualizar al final de cada mes.

Owner

  • Name: Francisco
  • Login: fralfaro
  • Kind: user

Citation (CITATION.cff) 

cff-version: 1.2.0
message: "Si usas este curso en tu investigación o trabajo, por favor cítalo como sigue:"
title: "MAT281 - Matemáticas Aplicadas"
authors:
  - family-names: "Alfaro"
    given-names: "Francisco"
    orcid: "https://orcid.org/0009-0003-7255-466X"
date-released: "2025-03-06"
version: "1.0.0"
doi: "10.5281/zenodo.14984124"
url: "https://github.com/fralfaro/MAT281"
license: "MIT"

GitHub Events

Total
  • Create event: 5
  • Issues event: 1
  • Release event: 1
  • Watch event: 34
  • Delete event: 1
  • Push event: 46
Last Year
  • Create event: 5
  • Issues event: 1
  • Release event: 1
  • Watch event: 34
  • Delete event: 1
  • Push event: 46

Issues and Pull Requests

Last synced: over 1 year ago

All Time
  • Total issues: 2
  • Total pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Total issue authors: 2
  • Total pull request authors: 0
  • Average comments per issue: 0.0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 2
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 2
  • Pull request authors: 0
  • Average comments per issue: 0.0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • vcanalesp (1)
  • fralfaro (1)
Pull Request Authors
Top Labels
Issue Labels
bug (2)
Pull Request Labels

Dependencies

.github/workflows/documentation.yml actions
  • actions/checkout v2 composite
  • actions/setup-python v2 composite
  • peaceiris/actions-gh-pages v3 composite
pyproject.toml pypi
  • mkdocs-jupyter 0.24.7
  • mkdocs-material 9.5.25
  • neoteroi-mkdocs 1.0.4
  • python ^3.10
.devcontainer/Dockerfile docker
  • python 3.10-slim build
.devcontainer/requirements.txt pypi
  • ipykernel * development
  • jupyter * development
  • loguru * development
  • matplotlib * development
  • numpy * development
  • pandas * development
  • python-dotenv * development
  • scikit-learn * development
  • seaborn * development
  • streamlit * development
requirements.txt pypi
  • ipykernel *
  • jupyter *
  • loguru *
  • matplotlib *
  • numpy *
  • pandas *
  • python-dotenv *
  • scikit-learn *
  • seaborn *
  • streamlit *