A 3-course Specialization from Coursera

Save For Later

Probabilistic Graphical Models

Save For Later

Probabilistic Graphical Models

About this Specialization

Probabilistic graphical models (PGMs) are a rich framework for encoding probability distributions over complex domains: joint (multivariate) distributions over large numbers of random variables that interact with each other. These representations sit at the intersection of statistics and computer science, relying on concepts from probability theory, graph algorithms, machine learning, and more. They are the basis for the state-of-the-art methods in a wide variety of applications, such as medical diagnosis, image understanding, speech recognition, natural language processing, and many, many more. They are also a foundational tool in formulating many machine learning problems.

Coursera

&

Stanford University

From Stanford University via Coursera
Hours 72
Instructor Daphne Koller
Language English
Subjects Programming Data Science

Similar Courses

Sorted by relevance

Careers

An overview of related careers and their average salaries in the US. Bars indicate income percentile (33rd - 99th).

Research Scientist-Machine Learning $55k

Cloud Architect - Azure / Machine Learning $75k

Watson Machine Learning Engineer $81k

Machine Learning Software Developer $103k

Software Engineer (Machine Learning) $116k

Applied Scientist, Machine Learning $130k

Autonomy and Machine Learning Solutions Architect $131k

Applied Scientist - Machine Learning -... $136k

RESEARCH SCIENTIST (MACHINE LEARNING) $147k

Machine Learning Engineer 2 $161k

Machine Learning Scientist Manager $170k

Machine Learning Scientist, Personalization $213k

Courses in this Specialization

Listed in the order in which they should be taken

Starts Course Information

Aug
10

Probabilistic Graphical Models 1: Representation

Probabilistic graphical models (PGMs) are a rich framework for encoding probability distributions over complex domains: joint (multivariate) distributions over large numbers of...

Coursera | Stanford University

Take just this course
For $79
Save

Aug
24

Probabilistic Graphical Models 2: Inference (You were viewing this course)

Probabilistic graphical models (PGMs) are a rich framework for encoding probability distributions over complex domains: joint (multivariate) distributions over large numbers of...

Coursera | Stanford University

Take just this course
For $79
Save

Aug
10

Probabilistic Graphical Models 3: Learning

Probabilistic graphical models (PGMs) are a rich framework for encoding probability distributions over complex domains: joint (multivariate) distributions over large numbers of...

Coursera | Stanford University

Take just this course
For $79
Save

Coursera

&

Stanford University

From Stanford University via Coursera
Hours 72
Instructor Daphne Koller
Language English
Subjects Programming Data Science

Careers

An overview of related careers and their average salaries in the US. Bars indicate income percentile (33rd - 99th).

Research Scientist-Machine Learning $55k

Cloud Architect - Azure / Machine Learning $75k

Watson Machine Learning Engineer $81k

Machine Learning Software Developer $103k

Software Engineer (Machine Learning) $116k

Applied Scientist, Machine Learning $130k

Autonomy and Machine Learning Solutions Architect $131k

Applied Scientist - Machine Learning -... $136k

RESEARCH SCIENTIST (MACHINE LEARNING) $147k

Machine Learning Engineer 2 $161k

Machine Learning Scientist Manager $170k

Machine Learning Scientist, Personalization $213k

Similar Courses

Sorted by relevance