explanation
The Probabilistic Graphical Models specialization is a set of specialized probabilistic graphical models training courses. Probabilistic graphical models are a rich framework for decoding probability distributions. The concepts of this course are actually common chapters in statistics and data science, building on concepts such as probability theory, graph algorithms, machine learning, etc. It is the basis for state-of-the-art technological methods, including a wide range of applications including medical diagnosis, image recognition, speech recognition, and natural language processing.
Skills you can learn from the Probabilistic Graphics Models specialization set:
- inference
- Bayesian network
- spread the faith
- drawing model
- Markov random field
- Gibbs sampling
- Markov Chain Monte Carlo (MCMC)
- algorithm
- Expectation – Maximization (EM) calculation
Course details:
Publisher: Coursera
teacher: Daphne Koller
Language:English
Education level: advanced
Number of courses: 3
Period: Assuming 11 hours a week, 4 months
Probabilistic Graphical Models Specialization Series Courses:
Course 1
Probabilistic Graphical Model 1: Representation
course 2
Probabilistic Graphical Model 2: Inference
Course 3
Probabilistic Graphical Model 3: Learning
Prerequisites for a stochastic graphical model:
This class requires abstract thinking and mathematical skills. However, it is designed to require little background knowledge, and motivated students can pick up background material as concepts are introduced. We want everyone to be able to understand all the core material using our new learning platform.
However, you must be able to program in at least one programming language and have a computer (Windows, Mac, or Linux) with access to the Internet (programming assignments will be performed in Matlab or Octave). It will also help you gain early exposure to the basic concepts of discrete probability theory (independence, conditional independence, and Bayes’ rule).
movie
Sample video probabilistic graphics model:
installation manual
After extracting, watch with your favorite players.
English subtitles
Quality: 720p
This collection includes three courses:
download link
Probabilistic Graphical Model 1: Representation
Probabilistic Graphical Model 2: Inference
Probabilistic Graphical Model 3: Learning
File password: free download software
size
Total approximately 2.1GB