Description
Probabilistic Graphical Models Specialization is a set of specialization courses for graphical probabilistic models. Probabilistic graphical models are a rich framework for decoding probability distributions. The concepts of this course are actually the intersection of statistics and data science based on concepts of probability theory, graph algorithms, machine learning and other cases. These are the foundations and methods of the latest technologies, which have various applications, including medical diagnostics, image recognition, speech recognition, natural language processing, and more.
The skills you will learn in the Probabilistic Graphical Models Specialization:
- Inference
- Bayesian network
- Belief Propagation
- Drawing models
- Markov Random Field
- Sampling Gibbs
- Markov Chain Monte Carlo (MCMC)
- Algorithms
- Algorithm Expectation-Maximization (EM)
Course details:
Publisher: Coursera
teacher: Daphne Koller
English language
Training level: advanced
Number of courses: 3
Duration: assuming 11 hours of work per week, 4 months
Courses available in Probabilistic Graphical Models Specialization:
COURSE 1
Probabilistic Graphical Models 1: Representation
COURSE 2
Probabilistic Graphical Models 2: Inference
COURSE 3
Probabilistic Graphical Models 3: Learning
Prerequisites of the Probabilistic Graphical Models course:
This class requires some abstract thinking and mathematical skills. However, it is designed to require fairly little background, and a motivated student can pick up the background material as the concepts are introduced. We hope that, using our new learning platform, it should be possible for everyone to understand all of the core material.
Although, you should be able to program in at least one programming language and have a computer (Windows, Mac or Linux) with internet access (programming assignments will be conducted in Matlab or Octave). It also helps to have some previous exposure to basic concepts in discrete probability theory (independence, conditional independence, and Bayes’ rule).
Pictures
Sample video of Probabilistic Graphical Models:
Installation guide
After Extract, view with your favorite Player.
English subtitle
Quality: 720p
This collection includes 3 different courses.
download link
Probabilistic Graphical Models 1: Representation
Probabilistic Graphical Models 2: Inference
Probabilistic Graphical Models 3: Learning
Password file(s): www.downloadly.ir
Size
About 2.1 GB in total
Be the first to comment