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  • Bayesian Statistics Techniques And Models

Results for "bayesian statistics: techniques and models"


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    Stanford University

    Probabilistic Graphical Models 3: Learning

    Skills you'll gain: Bayesian Network, Applied Machine Learning, Machine Learning Algorithms, Markov Model, Machine Learning, Statistical Modeling, Unstructured Data, Statistical Methods, Probability & Statistics, Algorithms, Test Data

    4.6
    Rating, 4.6 out of 5 stars
    ·
    303 reviews

    Advanced · Course · 1 - 3 Months

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    Northeastern University

    Statistical Learning for Engineering Part 1

    Skills you'll gain: Unsupervised Learning, Supervised Learning, Regression Analysis, Applied Machine Learning, Statistical Modeling, Machine Learning Algorithms, PyTorch (Machine Learning Library), Statistical Methods, Statistical Machine Learning, Machine Learning, Predictive Analytics, Predictive Modeling, Statistical Programming, Artificial Intelligence and Machine Learning (AI/ML), Deep Learning, Probability & Statistics, Dimensionality Reduction

    Intermediate · Course · 1 - 3 Months

  • C

    Coursera

    Using probability distributions for real world problems in R

    Skills you'll gain: Statistical Inference, Probability Distribution, R Programming, Statistical Visualization, Statistics, Data Visualization, Statistical Analysis, Statistical Modeling, Statistical Hypothesis Testing, Data Analysis, Probability

    4.8
    Rating, 4.8 out of 5 stars
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    32 reviews

    Beginner · Guided Project · Less Than 2 Hours

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    U

    University of Leeds

    Exploratory Data Analysis

    Skills you'll gain: Exploratory Data Analysis, Data Cleansing, Statistical Methods, Statistical Modeling, Data Visualization, Statistics, R (Software), Data Analysis, Descriptive Statistics, Box Plots, Data Visualization Software, Histogram, Probability, Probability Distribution

    4.6
    Rating, 4.6 out of 5 stars
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    9 reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
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    U

    University of Washington

    Practical Predictive Analytics: Models and Methods

    Skills you'll gain: Unsupervised Learning, Supervised Learning, Predictive Analytics, Statistical Modeling, R Programming, Statistical Methods, Decision Tree Learning, Statistical Inference, Statistical Analysis, Machine Learning Algorithms, Machine Learning, Graph Theory, Probability & Statistics, Network Analysis, Big Data, Sampling (Statistics), Random Forest Algorithm

    4.1
    Rating, 4.1 out of 5 stars
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    322 reviews

    Mixed · Course · 1 - 4 Weeks

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    Imperial College London

    Interventions and Calibration

    Skills you'll gain: Mathematical Modeling, Epidemiology, Infectious Diseases, Statistical Modeling, Data Modeling, R Programming, Differential Equations, Statistical Methods, Public Health, Probability & Statistics

    4.7
    Rating, 4.7 out of 5 stars
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    56 reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
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    D

    DeepLearning.AI

    Applied Statistics for Data Analytics

    Skills you'll gain: Probability & Statistics, Statistical Analysis, Statistics, Data Visualization, Statistical Hypothesis Testing, Descriptive Statistics, Data Analysis, Statistical Methods, Probability Distribution, Correlation Analysis, Statistical Inference, Sampling (Statistics), Large Language Modeling, LLM Application

    4.9
    Rating, 4.9 out of 5 stars
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    48 reviews

    Beginner · Course · 1 - 4 Weeks

  • C

    Coursera

    Essential Causal Inference Techniques for Data Science

    Skills you'll gain: Regression Analysis, Data Science, Machine Learning Methods, R Programming, Statistical Inference, Applied Machine Learning, Machine Learning, Statistical Methods, Advanced Analytics, Data Analysis, Predictive Modeling

    4.5
    Rating, 4.5 out of 5 stars
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    39 reviews

    Beginner · Guided Project · Less Than 2 Hours

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    Northeastern University

    Engineering Probability and Statistics Part 2

    Skills you'll gain: Statistical Hypothesis Testing, Statistical Inference, Sampling (Statistics), Statistical Reporting, Statistical Methods, Probability & Statistics, Statistical Analysis, Experimentation, Data Analysis, Data Presentation, Estimation

    Mixed · Course · 1 - 3 Months

  • Status: New
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    Northeastern University

    Statistical Learning for Engineering Part 2

    Skills you'll gain: PyTorch (Machine Learning Library), Applied Machine Learning, Unsupervised Learning, Reinforcement Learning, Supervised Learning, Machine Learning Algorithms, Dimensionality Reduction, Statistical Machine Learning, Machine Learning, Machine Learning Software, Artificial Neural Networks, Artificial Intelligence and Machine Learning (AI/ML), Deep Learning, Classification And Regression Tree (CART), Random Forest Algorithm, Generative Model Architectures

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
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    S

    SAS

    Modeling Time Series and Sequential Data

    Skills you'll gain: Time Series Analysis and Forecasting, SAS (Software), Forecasting, Regression Analysis, Applied Machine Learning, Statistical Analysis, Advanced Analytics, Statistical Methods, Predictive Modeling, Statistical Modeling, Bayesian Statistics, Artificial Neural Networks

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
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    J

    Johns Hopkins University

    Mathematical Biostatistics Boot Camp 2

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

    4.3
    Rating, 4.3 out of 5 stars
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    136 reviews

    Mixed · Course · 1 - 4 Weeks

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In summary, here are 10 of our most popular bayesian statistics: techniques and models courses

  • Probabilistic Graphical Models 3: Learning: Stanford University
  • Statistical Learning for Engineering Part 1: Northeastern University
  • Using probability distributions for real world problems in R: Coursera
  • Exploratory Data Analysis: University of Leeds
  • Practical Predictive Analytics: Models and Methods: University of Washington
  • Interventions and Calibration: Imperial College London
  • Applied Statistics for Data Analytics: DeepLearning.AI
  • Essential Causal Inference Techniques for Data Science: Coursera
  • Engineering Probability and Statistics Part 2: Northeastern University
  • Statistical Learning for Engineering Part 2: Northeastern University

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