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  • Bayesian Network

Results for "bayesian+network"


  • Status: Free Trial
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    J

    Johns Hopkins University

    Foundations of Probability and Random Variables

    Skills you'll gain: R Programming, Statistical Analysis, Statistical Programming, Data Analysis, Probability, Probability Distribution, Applied Machine Learning, Probability & Statistics, Applied Mathematics, Data Science, Computational Thinking, Simulations

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    U

    University of California, Santa Cruz

    Bayesian Statistics: Capstone Project

    Skills you'll gain: Bayesian Statistics, Technical Communication, Data Presentation, R Programming, Statistical Analysis, Statistical Modeling, Data Analysis, Time Series Analysis and Forecasting, Statistical Inference, Sampling (Statistics), Model Evaluation, Probability Distribution

    4.4
    Rating, 4.4 out of 5 stars
    ·
    9 reviews

    Advanced · Course · 1 - 4 Weeks

  • Status: Free Trial
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    U

    University of Colorado Boulder

    Discrete-Time Markov Chains and Monte Carlo Methods

    Skills you'll gain: Artificial Intelligence, Generative AI, Machine Learning Algorithms, Mathematical Theory & Analysis

    Build toward a degree

    4.9
    Rating, 4.9 out of 5 stars
    ·
    8 reviews

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    U

    University of California, Santa Cruz

    Bayesian Statistics: Mixture Models

    Skills you'll gain: R Programming, Statistical Modeling, Bayesian Statistics, Statistical Software, Markov Model, Mathematical Modeling, Statistical Methods, Probability & Statistics, Unsupervised Learning, Machine Learning Methods, Probability Distribution, Classification Algorithms

    4.5
    Rating, 4.5 out of 5 stars
    ·
    62 reviews

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    U

    University of Pittsburgh

    Probability Theory and Regression for Predictive Analytics

    Skills you'll gain: Probability Distribution, Data Science, Probability & Statistics, Predictive Analytics, Probability, Statistical Modeling, Data Analysis, Regression Analysis, Logistic Regression, Statistical Analysis, Statistical Methods, Statistical Machine Learning, Bayesian Statistics, Statistical Inference, Feature Engineering, Applied Mathematics, Python Programming, Machine Learning, Algorithms

    Build toward a degree

    Beginner · Course · 1 - 4 Weeks

  • Status: New
    New
    Status: Free Trial
    Free Trial
    K

    KodeKloud

    Data Engineering Essentials

    Skills you'll gain: MLOps (Machine Learning Operations), Apache Kafka, Apache Airflow, Apache Spark, Extract, Transform, Load, Data Lakes, Data Pipelines, Distributed Computing, Real Time Data, DevOps, Big Data, Data Preprocessing, Feature Engineering, Model Deployment, CI/CD, Pandas (Python Package), Data Transformation

    Beginner · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    L

    LearnQuest

    Neural Networks and Random Forests

    Skills you'll gain: Model Evaluation, Random Forest Algorithm, Keras (Neural Network Library), Tensorflow, Deep Learning, Artificial Neural Networks, Decision Tree Learning, Scikit Learn (Machine Learning Library), Machine Learning, Regression Analysis, Classification Algorithms, Python Programming

    3.3
    Rating, 3.3 out of 5 stars
    ·
    17 reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    S

    Stanford University

    Probabilistic Graphical Models 2: Inference

    Skills you'll gain: Bayesian Network, Machine Learning Methods, Statistical Inference, Markov Model, Graph Theory, Sampling (Statistics), Applied Machine Learning, Statistical Methods, Probability & Statistics, Algorithms, Probability Distribution, Machine Learning Algorithms, Computational Thinking

    4.6
    Rating, 4.6 out of 5 stars
    ·
    489 reviews

    Advanced · Course · 1 - 3 Months

  • Status: Preview
    Preview
    C

    Columbia University

    Causal Inference

    Skills you'll gain: Statistical Inference, Regression Analysis, Statistical Methods, Sampling (Statistics), Statistical Modeling, Machine Learning, Experimentation, Data Collection, Probability & Statistics, Research Design, Econometrics, Program Evaluation, Logistic Regression

    3.3
    Rating, 3.3 out of 5 stars
    ·
    104 reviews

    Advanced · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    S

    Stanford University

    Probabilistic Graphical Models 3: Learning

    Skills you'll gain: Bayesian Network, Applied Machine Learning, Machine Learning Algorithms, Bayesian Statistics, Markov Model, Machine Learning, Statistical Modeling, Probability Distribution, Statistical Methods, Algorithms, Model Evaluation

    4.6
    Rating, 4.6 out of 5 stars
    ·
    304 reviews

    Advanced · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    J

    Johns Hopkins University

    Mathematical Biostatistics Boot Camp 1

    Skills you'll gain: Sampling (Statistics), Bayesian Statistics, Probability & Statistics, Statistical Inference, Statistical Methods, Statistics, Probability, Probability Distribution, Statistical Analysis, Biostatistics, Statistical Hypothesis Testing

    4.4
    Rating, 4.4 out of 5 stars
    ·
    539 reviews

    Mixed · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    S

    Simplilearn

    Introduction Course to Autoencoders, VAEs, and GANs

    Skills you'll gain: Generative Adversarial Networks (GANs), Generative AI, Autoencoders, Deep Learning, Convolutional Neural Networks, Tensorflow, Unsupervised Learning, Dimensionality Reduction, Model Evaluation

    Beginner · Course · 1 - 4 Weeks

1…456…9

In summary, here are 10 of our most popular bayesian+network courses

  • Foundations of Probability and Random Variables: Johns Hopkins University
  • Bayesian Statistics: Capstone Project: University of California, Santa Cruz
  • Discrete-Time Markov Chains and Monte Carlo Methods: University of Colorado Boulder
  • Bayesian Statistics: Mixture Models: University of California, Santa Cruz
  • Probability Theory and Regression for Predictive Analytics: University of Pittsburgh
  • Data Engineering Essentials: KodeKloud
  • Neural Networks and Random Forests: LearnQuest
  • Probabilistic Graphical Models 2: Inference: Stanford University
  • Causal Inference: Columbia University
  • Probabilistic Graphical Models 3: Learning: Stanford University

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