¿Qué está mal?

Aviso: Antes de informar sobre un error con la descarga, por favor, prueba el enlace directo: A First Encounter with Machine Learning

Cargando...

Debes iniciar sesión para hacer esto.

A First Encounter with Machine Learning

A First Encounter with Machine Learning

A First Encounter with Machine Learning

Puntuación: ---- | 0 votos
| Enviando voto
| ¡Votado!
|

Detalles del libro:

pos
Global
pos
Categoría
Año:2011
Editor:University of California Irvine
Páginas:93 páginas
Idioma:inglés
Desde:07/05/2015
Tamaño:368 KB
Licencia:Pendiente de revisión

Contenido:

In winter quarter 2007 I taught an undergraduate course in machine learning at UC Irvine. While I had been teaching machine learning at a graduate level it became soon clear that teaching the same material to an undergraduate class was a whole new challenge. Much of machine learning is build upon concepts from mathematics such as partial derivatives, eigenvalue decompositions, multivariate probability densities and so on. I quickly found that these concepts could not be taken for granted at an undergraduate level. The situation was aggravated by the lack of a suitable textbook. Excellent textbooks do exist for this field, but I found all of them to be too technical for a first encounter with machine learning.

This experience led me to believe there was a genuine need for a simple, intuitive introduction into the concepts of machine learning. A first read to wet the appetite so to speak, a prelude to the more technical and advanced textbooks. Hence, the book you see before you is meant for those starting out in the field who need a simple, intuitive explanation of some of the most useful algorithms that our field has to offer.

Machine learning is a relatively recent discipline that emerged from the general field of artificial intelligence only quite recently. To build intelligent machines researchers realized that these machines should learn from and adapt to their environment. It is simply too costly and impractical to design intelligent systems by first gathering all the expert knowledge ourselves and then hard-wiring it into a machine. For instance, after many years of intense research the we can now recognize faces in images to a high degree accuracy.

Categorías:

Etiquetas:

Cargando comentarios...

Escaneando listas...

El libro en números

Posición global

posición en categoría

en catálogo desde

07/05/2015

puntuación

Nothing yet...

votos

Nothing yet...

'LIKES' sociales

Nothing yet...

Visitas

Descargas

Esto puede tardar un momento

Interés

Segmentación por países

Esto puede tardar un momento

Páginas de entrada

Segmentación por sitios web

evolución

Esto puede tardar un momento

Cargando...