Repositorio de los Laboratorios de Análisis Numérico / Análisis Numérico I de FAMAF, UNC.

Last update: Dec 12, 2022

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Overview

Repositorio de los Laboratorios de Análisis Numérico / Análisis Numérico I de FAMAF, UNC.

Para los Laboratorios de la materia, vamos a utilizar el lenguaje de programación Python 3.X (donde X puede ser cualquier número mayor o igual a 5).

Tutorial para crear cuentas de UNC alumnos en este enlace.
Para instalar Python en sus computadoras, pueden seguir la página https://tutorial.djangogirls.org/es/python_installation/, tiene un buen tutorial para comenzar. En caso de querer una ayuda un poco más visual, recomendamos seguir este video.
Para poder crear el código que van a ejecutar, les recomendamos utilizar Visual Studio Code: https://code.visualstudio.com/. Este editor tiene la capacidad de agregar extensiones que facilitan un poco el trabajo con Python, pueden buscar la extensión llamada Python que aparece en la sección de Extensiones una vez que tengan instalado VSCode.
Para aquellas personas que solamente puedan usar el celular para realizar los laboratorios, es posible descargar la aplicación Google Colab Android View (Enlace a Google Play), que les permite utilizar y ejecutar código Python en celdas.

Playlists de Clases de Ediciones Anteriores

Owner

Luis Biedma

Mathematician and Data Scientist.

Luis Biedma

GitHub Repository

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Pseudo lidar - (CVPR 2019) Pseudo-LiDAR from Visual Depth Estimation: Bridging the Gap in 3D Object Detection for Autonomous Driving

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catch-22: CAnonical Time-series CHaracteristics

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Open-source code for Generic Grouping Network (GGN, CVPR 2022)

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[CVPR 2021] Involution: Inverting the Inherence of Convolution for Visual Recognition, a brand new neural operator

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Mortgage-loan-prediction - Show how to perform advanced Analytics and Machine Learning in Python using a full complement of PyData utilities

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