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  • Bayesian Network

Results for "bayesian+network"


  • Status: Preview
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    U

    Universidad Nacional Autónoma de México

    Estadística y probabilidad: principios de Inferencia

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

    3.1
    Rating, 3.1 out of 5 stars
    ·
    16 reviews

    Beginner · Course · 1 - 4 Weeks

  • Status: Preview
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    C

    Columbia University

    Causal Inference 2

    Skills you'll gain: Statistical Inference, Econometrics, Mediation, Advanced Analytics, Statistical Analysis, Regression Analysis, Time Series Analysis and Forecasting, Statistical Methods, Statistical Modeling, Research Design

    3.3
    Rating, 3.3 out of 5 stars
    ·
    15 reviews

    Advanced · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    J

    Johns Hopkins University

    Computational and Graphical Models in Probability

    Skills you'll gain: Network Analysis, Statistical Modeling, Bayesian Network, R (Software), R Programming, Social Network Analysis, Simulations, Graph Theory, Statistical Analysis, Probability & Statistics, Markov Model, Probability Distribution, Data Visualization, Machine Learning, Statistical Hypothesis Testing

    Intermediate · Course · 1 - 4 Weeks

  • Status: Preview
    Preview
    G

    Google Cloud

    Using BigQuery Machine Learning for inference

    Skills you'll gain: Data Analysis, Big Data, Applied Machine Learning, Google Cloud Platform, Machine Learning Algorithms, Machine Learning

    Beginner · Course · 1 - 4 Weeks

  • Status: New
    New
    Status: Free Trial
    Free Trial
    E

    EDUCBA

    Machine Learning with R: Build, Analyze & Predict

    Skills you'll gain: Data Analysis, Statistical Analysis, Probability Distribution, R Programming, Exploratory Data Analysis, Statistical Modeling, Machine Learning, Statistical Inference, Classification Algorithms, Data Manipulation, Supervised Learning, Random Forest Algorithm, Regression Analysis, Model Evaluation, Decision Tree Learning

    Mixed · Course · 1 - 4 Weeks

  • Status: New
    New
    G

    Google Cloud

    Deploy and Scale AI Models with Cloud Run

    Skills you'll gain: Google Cloud Platform, Model Deployment, Serverless Computing, Cloud Deployment, Generative AI, MLOps (Machine Learning Operations), Containerization, Performance Tuning, Scalability

    Beginner · 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
    ·
    488 reviews

    Advanced · Course · 1 - 3 Months

  • Status: New
    New
    Status: Free Trial
    Free Trial
    E

    EDUCBA

    Machine Learning with Python & Statistics

    Skills you'll gain: Sampling (Statistics), Data Mining, Statistical Hypothesis Testing, Probability, Linear Algebra, Statistical Analysis, Statistical Inference, Data Analysis, Probability Distribution, Statistics, Machine Learning Algorithms, Machine Learning, Python Programming

    Mixed · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    P

    Packt

    Foundations of Deep Learning and Neural Networks

    Skills you'll gain: Artificial Neural Networks, Deep Learning, Convolutional Neural Networks, Image Analysis, Keras (Neural Network Library), Artificial Intelligence and Machine Learning (AI/ML), Tensorflow, Machine Learning Methods, Network Architecture, Artificial Intelligence, Network Model, Machine Learning, Classification Algorithms, Data Processing

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    J

    Johns Hopkins University

    Introduction to Neural Networks

    Skills you'll gain: Convolutional Neural Networks, Artificial Neural Networks, Deep Learning, Machine Learning Algorithms, Image Analysis, Machine Learning, Computer Vision, Model Evaluation, Supervised Learning, Algorithms, Statistical Methods, Linear Algebra, Probability

    4.3
    Rating, 4.3 out of 5 stars
    ·
    6 reviews

    Intermediate · Course · 1 - 3 Months

  • Status: New
    New
    Status: Preview
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    P

    Packt

    Machine Learning with PyTorch and Scikit-Learn

    Skills you'll gain: Reinforcement Learning, Dimensionality Reduction, PyTorch (Machine Learning Library), Machine Learning Algorithms, Data Preprocessing, Model Evaluation, Artificial Intelligence and Machine Learning (AI/ML), Generative Adversarial Networks (GANs), Machine Learning Methods, Deep Learning, Transfer Learning, Applied Machine Learning, Pandas (Python Package), Scikit Learn (Machine Learning Library), Python Programming, Machine Learning, Artificial Neural Networks, Data Processing, Natural Language Processing, Feature Engineering

    Intermediate · Course · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    S

    Simplilearn

    Deep Learning Frameworks and Neural Networks Simplified

    Skills you'll gain: Recurrent Neural Networks (RNNs), Model Deployment, Keras (Neural Network Library), Deep Learning, Tensorflow, Artificial Neural Networks, Convolutional Neural Networks, Application Frameworks, Artificial Intelligence, Machine Learning Methods, Image Analysis, Data Preprocessing

    Beginner · Course · 1 - 4 Weeks

1…567…9

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

  • Estadística y probabilidad: principios de Inferencia: Universidad Nacional Autónoma de México
  • Causal Inference 2: Columbia University
  • Computational and Graphical Models in Probability: Johns Hopkins University
  • Using BigQuery Machine Learning for inference: Google Cloud
  • Machine Learning with R: Build, Analyze & Predict: EDUCBA
  • Deploy and Scale AI Models with Cloud Run: Google Cloud
  • Probabilistic Graphical Models 2: Inference: Stanford University
  • Machine Learning with Python & Statistics: EDUCBA
  • Foundations of Deep Learning and Neural Networks: Packt
  • Introduction to Neural Networks: Johns Hopkins University

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