Creada por:   Stanford University

  • Daphne Koller

    Enseñado por:    Daphne Koller, Professor

    School of Engineering
Información básica
Curso 1 de 3 en el Programa especializado Probabilistic Graphical Models .
NivelAdvanced
Idioma
English
Cómo aprobarAprueba todas las tareas calificadas para completar el curso.
Calificaciones del usuario
4.7 stars
Average User Rating 4.7Ve los que los estudiantes dijeron
Programa

Preguntas Frecuentes
Cómo funciona
Trabajo del curso
Trabajo del curso

Cada curso es como un libro de texto interactivo, con videos pregrabados, cuestionarios y proyectos.

Ayuda de tus compañeros
Ayuda de tus compañeros

Conéctate con miles de estudiantes y debate ideas y materiales del curso, y obtén ayuda para dominar los conceptos.

Certificados
Certificados

Obtén reconocimiento oficial por tu trabajo y comparte tu éxito con amigos, compañeros y empleadores.

Creadores
Stanford University
The Leland Stanford Junior University, commonly referred to as Stanford University or Stanford, is an American private research university located in Stanford, California on an 8,180-acre (3,310 ha) campus near Palo Alto, California, United States.
Tarifa
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Accede a los materiales del curso

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Accede a los materiales con calificación

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Recibe una calificación final

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Obtén un Certificado para compartir

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Calificaciones y revisiones
Calificado 4.7 de 5 371 calificaciones

Everything is explained very clearly throughout the course, and the structure they use to teach the subject , from basics to advanced material, is especially helpful. Would recommend this course to anyone with an interest in probabilistic modelling.

it's really hard course for me but after completing and see the certificate I feel so good about it. Yesterday someone asked a question regarding conditional independence. I remember before I took the course I've spent quite some time understanding it, just like him. But yesterday I didn't event think about it and gave him the right answer using "active trail" and "D-separation" concept. That's how powerful this course can be.

I didn't work on the honor track though because I'm currently short of time. But I think I will come back and taking the other 2 courses in this series.

One of the best courses which i visited.

The explanation was so simple and there were many examples which were so helpful for me

A five stars course. Prof. Koller is an outstanding scientists in this field. The first part just introduce you two basic frames of graphical models. So go further into second part is necessary if you want to have a bigger picture. The whole course is an introduction to the book - Probabilistic Graphical Models of Prof. Koller, so buying her book is also highly recommended. This course is supposed to be hard, so you should expect a steep learning curve. But all the efforts you made are worthy. I suggest coursera will consider put more challenging exercises in order to extent the concentration. Finally, a highly respect to Prof. Koller who provide the course in such a theoretical depth.