September 2024
Intermediate to advanced
328 pages
8h 54m
Spanish
Content preview from Álgebra lineal práctica para la ciencia de datos
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Capítulo 6. Matrices, 2ª parte
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La multiplicación de matrices es uno de los dones más maravillosos que nos han concedido los matemáticos. Pero para pasar del álgebra lineal elemental a la avanzada -y luego para comprender y desarrollar algoritmos de ciencia de datos- necesitas hacer algo más que multiplicar matrices.
Empezaremos este capítulo hablando de las normas matriciales y los espacios matriciales. Las normas matriciales son esencialmente una extensión de las normas vectoriales, y los espacios matriciales son esencialmente una extensión de los subespacios vectoriales (que a su vez no son más que combinaciones lineales ponderadas). Así que ya tienes los conocimientos básicos necesarios para este capítulo.
Conceptos como independencia lineal, rango y determinante te permitirán pasar de la comprensión de conceptos elementales como transposición y multiplicación a la comprensión de temas avanzados como inversa, valores propios y valores singulares. Y esos temas avanzados desvelan el poder del álgebra lineal para aplicaciones en la ciencia de datos. Por tanto, este capítulo es un punto de inflexión en tu transformación de novato en álgebra lineal a experto en álgebra lineal.1
Las matrices parecen cosas tan sencillas como una hoja de cálculo con números. Pero ya has visto en los capítulos anteriores que las matrices son mucho más de lo que parece. Así que respira ...
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