Probabilistic Graphical Models Specialization

Probabilistic Graphical Models Specialization

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Acquire a novel approach to learning and reasoning in intricate fields.

Key AI Functions:Inference,Bayesian Network,Belief Propagation,Graphical Model

Description for Probabilistic Graphical Models Specialization

Features of Course

  • Learning a novel approach to comprehending and reasoning in complex fields: Graphical Models of Probability.
  • Probabilistic Graphical Models (PGMs): Investigate a comprehensive framework for encoding probability distributions across complex domains.
  • Foundational Concepts: Investigate the intersection of graph algorithms, probability theory, and machine learning to address intricate AI issues.
  • Diverse Applications: Utilize PGMs in a variety of disciplines, such as medical diagnosis, image comprehension, speech recognition, and natural language processing.
  • Level: Advanced

    Certification Degree: Yes

    Languages the Course is Available: 22

    Offered by: On Coursera provided by Stanford

    Duration: 4 months at 10 hours a week

    Schedule: Flexible

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