Created by:   Stanford University

  • Daphne Koller

    Taught by:    Daphne Koller, Professor

    School of Engineering

Basic InfoCourse 1 of 3 in the Probabilistic Graphical Models Specialization.
LevelAdvanced
Language
English
How To PassPass all graded assignments to complete the course.
User Ratings
4.7 stars
Average User Rating 4.7See what learners said
Course 1 of Specialization
Probabilistic Graphical Models. Master a new way of reasoning and learning in complex domains
Syllabus

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Learning Outcomes: By the end of this course, you will be able to

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Coursework
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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.
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Ratings and Reviews
Rated 4.7 out of 5 of 294 ratings

The course is pretty good. I love the way that the professor led us into the graphical models.

Really Helpful for Studying!

Some more exam questions and variation, including explanations when failing, would be very useful.

Before I took this course I took the Stanford Machine Learning course, which I greatly enjoyed. That course allows for the learning of difficult concepts in a way that I found less painful than working through a textbook. In this course there is a lot less video content, and the coding assignments are less interesting. Expect to spend a lot of time understanding the nuances of the code that the instructional team has developed, and be prepared to really pore over the gritty aspects of Octave or MATLAB. If you're serious about this course I suggest buying the accompanying book. The slides are not easy to understand without the audio narration, which makes them difficult to review, and unlike the case in the ML course, there are not a lot of readily available open introductions written on the topics.