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Coursera Stanford University - Probabilistic Graphical Models (2018)
Coursera: Stanford University - Probabilistic Graphical Models
WEBRip | English | MP4 + PDF Slides | 960 x 540 | AVC ~39.6 kbps | 15 fps
AAC | 128 Kbps | 44.1 KHz | 2 channels | Subs: English (.srt) | 23:25:47 | 1.36 GB
Genre: eLearning Video / Computer Science, Engineering and Technology

Category: Tutorials | Keywords: Coursera, Stanford, University, Probabilistic, Graphical, Models Read More

Coursera Probabilistic Graphical Models

Coursera: Stanford University - Probabilistic Graphical Models
WEBRip | English | MP4 + PDF Slides | 960 x 540 | AVC ~39.6 kbps | 15 fps
AAC | 128 Kbps | 44.1 KHz | 2 channels | Subs: English (.srt) | 23:25:47 | 1.36 GB
Genre: eLearning Video / Computer Science, Engineering and Technology
What are Probabilistic Graphical Models? Uncertainty is unavoidable in real-world applications: we can almost never predict with certainty what will happen in the future, and even in the present and the past, many important aspects of the world are not observed with certainty. Probability theory gives us the basic foundation to model our beliefs about the different possible states of the world, and to update these beliefs as new evidence is obtained. These beliefs can be combined with individual preferences to help guide our actions, and even in selecting which observations to make. While probability theory has existed since the 17th century, our ability to use it effectively on large problems involving many inter-related variables is fairly recent, and is due largely to the development of a framework known as Probabilistic Graphical Models (PGMs).




Category: Tutorials | Keywords: Coursera, Probabilistic, Graphical, Models Read More
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