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  • Probabilistic Graphical Models

Probabilistic Graphical Models Courses

Probabilistic Graphical Models courses can help you learn Bayesian networks, Markov random fields, and inference algorithms. You can build skills in modeling uncertainty, reasoning under uncertainty, and making predictions based on incomplete data. Many courses introduce tools like TensorFlow Probability and PyMC3, which are used for implementing these models and performing complex calculations, enabling you to apply your knowledge to real-world data analysis and machine learning tasks.


Popular Probabilistic Graphical Models Courses and Certifications


  • Status: Free Trial
    Free Trial
    U

    University of Michigan

    Fitting Statistical Models to Data with Python

    Skills you'll gain: Statistical Modeling, Statistical Methods, Bayesian Statistics, Statistical Inference, Statistical Software, Model Evaluation, Statistical Analysis, Statistical Programming, Statistical Machine Learning, Regression Analysis, Predictive Modeling, Jupyter, Logistic Regression, Python Programming, Data Visualization Software

    4.4
    Rating, 4.4 out of 5 stars
    ·
    714 reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: New
    New
    Status: Preview
    Preview
    E

    EDUCBA

    Predictive Modeling with Python: Apply & Evaluate

    Skills you'll gain: Predictive Modeling, Model Evaluation, Data Preprocessing, Predictive Analytics, Logistic Regression, Risk Modeling, Statistical Modeling, Feature Engineering, Regression Analysis, Correlation Analysis, Classification Algorithms, Data Manipulation, Scikit Learn (Machine Learning Library), Data Transformation, Pandas (Python Package), NumPy

    Mixed · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    P

    Packt

    Advanced PyTorch Techniques and Applications

    Skills you'll gain: PyTorch (Machine Learning Library), Natural Language Processing, Generative Adversarial Networks (GANs), Transfer Learning, Vision Transformer (ViT), Deep Learning, Unsupervised Learning, Embeddings, Convolutional Neural Networks, Applied Machine Learning, Supervised Learning, Model Evaluation, Model Deployment, Flask (Web Framework)

    4.6
    Rating, 4.6 out of 5 stars
    ·
    16 reviews

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    J

    Johns Hopkins University

    Quantifying Relationships with Regression Models

    Skills you'll gain: Regression Analysis, Logistic Regression, Correlation Analysis, Statistical Inference, Model Evaluation, Statistical Modeling, Statistical Analysis, Probability & Statistics

    4.6
    Rating, 4.6 out of 5 stars
    ·
    23 reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    U

    University of Washington

    Practical Predictive Analytics: Models and Methods

    Skills you'll gain: Unsupervised Learning, Supervised Learning, Statistical Machine Learning, Predictive Analytics, Advanced Analytics, Data Analysis, R Programming, Statistical Methods, Statistical Inference, Statistical Analysis, Machine Learning Algorithms, Machine Learning, Graph Theory, Classification Algorithms, Probability & Statistics, Big Data

    4.1
    Rating, 4.1 out of 5 stars
    ·
    323 reviews

    Mixed · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    I

    IBM

    AI Workflow: Machine Learning, Visual Recognition and NLP

    Skills you'll gain: Model Evaluation, Tensorflow, Supervised Learning, Artificial Neural Networks, Regression Analysis, Machine Learning Methods, Applied Machine Learning, Machine Learning Algorithms, Deep Learning, Image Analysis, Machine Learning, Random Forest Algorithm, Artificial Intelligence and Machine Learning (AI/ML), Decision Tree Learning, Natural Language Processing, Scikit Learn (Machine Learning Library), Convolutional Neural Networks, Computer Vision, Data Science, Python Programming

    4.4
    Rating, 4.4 out of 5 stars
    ·
    90 reviews

    Advanced · Course · 1 - 4 Weeks

  • Status: Free
    Free
    C

    Coursera

    Tidymodels in R: Building tidy machine learning models

    Skills you'll gain: Tidyverse (R Package), Model Evaluation, Data Visualization, Clinical Data Management, Data Preprocessing, Data Manipulation, Predictive Modeling, R Programming, Predictive Analytics, Data Pipelines, Feature Engineering, Applied Machine Learning, Machine Learning, Random Forest Algorithm, Performance Tuning, Logistic Regression

    Intermediate · Guided Project · Less Than 2 Hours

  • Status: Free Trial
    Free Trial
    U

    University of Pennsylvania

    Modeling Risk and Realities

    Skills you'll gain: Risk Management, Mathematical Modeling, Predictive Modeling, Financial Modeling, Simulation and Simulation Software, Operations Research, Probability Distribution, Data-Driven Decision-Making, Statistical Hypothesis Testing, Statistical Analysis, Microsoft Excel, Excel Formulas

    4.6
    Rating, 4.6 out of 5 stars
    ·
    2.2K reviews

    Mixed · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    J

    Johns Hopkins University

    Modeling Data in the Tidyverse

    Skills you'll gain: Statistical Modeling, Exploratory Data Analysis, R Programming, Predictive Modeling, Statistical Hypothesis Testing, Tidyverse (R Package), Data Analysis, Data Modeling, Regression Analysis, Data Science, Classification And Regression Tree (CART), Statistical Inference, Statistical Analysis, Rmarkdown, Data Preprocessing, Statistical Methods, Model Evaluation, Machine Learning

    4.7
    Rating, 4.7 out of 5 stars
    ·
    10 reviews

    Mixed · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    P

    Packt

    Natural Language Processing - Probability Models in Python

    Skills you'll gain: Cryptography, Classification Algorithms, Probability Distribution, Machine Learning Algorithms, Data Processing, Algorithms

    Intermediate · Course · 1 - 4 Weeks

  • C

    Coursera

    Building Statistical Models in R: Linear Regression

    Skills you'll gain: Exploratory Data Analysis, Statistical Modeling, Regression Analysis, Data Visualization, Model Evaluation, Data Analysis, Statistical Methods, Scatter Plots, R Programming, Statistical Analysis, Plot (Graphics), R (Software), Ggplot2

    4.7
    Rating, 4.7 out of 5 stars
    ·
    20 reviews

    Beginner · Guided Project · Less Than 2 Hours

  • 2

    28DIGITAL

    Quantitative Model Checking

    Skills you'll gain: Computational Logic, Markov Model, Verification And Validation, Theoretical Computer Science, Mathematical Modeling, Systems Analysis, Statistical Modeling, Probability, Algorithms, Probability Distribution

    4.3
    Rating, 4.3 out of 5 stars
    ·
    54 reviews

    Intermediate · Course · 1 - 3 Months

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In summary, here are 10 of our most popular probabilistic graphical models courses

  • Fitting Statistical Models to Data with Python: University of Michigan
  • Predictive Modeling with Python: Apply & Evaluate: EDUCBA
  • Advanced PyTorch Techniques and Applications: Packt
  • Quantifying Relationships with Regression Models: Johns Hopkins University
  • Practical Predictive Analytics: Models and Methods: University of Washington
  • AI Workflow: Machine Learning, Visual Recognition and NLP: IBM
  • Tidymodels in R: Building tidy machine learning models: Coursera
  • Modeling Risk and Realities: University of Pennsylvania
  • Modeling Data in the Tidyverse: Johns Hopkins University
  • Natural Language Processing - Probability Models in Python: Packt

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