Algoritmos de Aprendizaje Supervisado en la Clasificación de Exoplanetas en Python

Currently there is a large number of databases, given the multiple sources such as: social networks, banking movements, consultations in web browsers for private, business or academic use. A clear example is the study of exoplanets carried out by NASA, through multiple sources such as ground-based o...

Full description

Saved in:

Bibliographic Details
Main Author:	González Cangrejo, Johans
Other Authors:	Orjuela Vargas, Sergio Alejandro
Format:	Trabajo de grado (Pregrado y/o Especialización)
Language:	spa
Published:	Universidad Antonio Nariño 2022
Subjects:	Machine Learning validación NASA exoplanetas observatorios aprendizaje supervisado, algoritmo validation exoplanets observatories supervised learning algorithm
Online Access:	http://repositorio.uan.edu.co/handle/123456789/5839
Tags:	Add Tag No Tags, Be the first to tag this record!

Description
Summary:	Currently there is a large number of databases, given the multiple sources such as: social networks, banking movements, consultations in web browsers for private, business or academic use. A clear example is the study of exoplanets carried out by NASA, through multiple sources such as ground-based observatories and space telescopes (NASA, 2021). It is important to mention that, at the time of starting this work, the aforementioned database contains 4512 confirmed planets; without a doubt, a quite important figure with enough potential to study in search of patterns and new knowledge that leads to new observations.