01833nam a2200313   450000500170000000600190001700800410003602000190007704000130009604100080010908200210011710000210013824500720015925000190023126400780025030000560032833600270038433700330041133800280044450001830047250501750065552005200083065000290135065000300137965000290140965000280143865000280146665000250149420260727085803.0a|||||r|||| 00| 0 260727b        |||||||| |||| 00| 0 spa d  a978-0262018029  aCO-ViULL  hspa04223a006.31bM9781 aMurphy, Kevin P.10aMachine learning :ba probabilistic perspective /cKevin P. Murphy.  a1ª edición. 1aCambridge, Massachusetts :bMassachusetts Institute of Technology,c2012.  a1071 páginas :bilustraciones,c24 centímetros.  2rdacontentatextobtxt  2rdamediaasin mediaciónbn  2rdacarrieravolumenbnc  aObra de referencia sobre aprendizaje automático con enfoque probabilístico, orientada a estudiantes, investigadores y profesionales de la informática y la ciencia de datos.0 aParte I. Fundamentos -- Parte II. Modelos probabilísticos -- Parte III. Aprendizaje supervisado -- Parte IV. Aprendizaje no supervisado -- Parte V. Métodos avanzados.  aA comprehensive introduction to machine learning that uses probabilistic models and inference as a unifying approach.
Today's Web-enabled deluge of electronic data calls for automated methods of data analysis. Machine learning provides these, developing methods that can automatically detect patterns in data and then use the uncovered patterns to predict future data. This textbook offers a comprehensive and self-contained introduction to the field of machine learning, based on a unified, probabilistic approach. 0aAprendizaje automático 0aModelos probabilísticos 0aAprendizaje automatizado 0aInteligencia artificial 0aAprendizaje supervisado 0aSistemas adaptativos