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  • Bayesian Linear Regression

Results for "bayesian linear regression"


  • Status: New
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    E

    EDUCBA

    Logistic Regression Fundamentals: Analyze & Predict

    Skills you'll gain: SAS (Software), Predictive Modeling, Regression Analysis, Analytics, Statistical Methods, Data Transformation, Statistical Analysis, Business Analytics, Logistics, Estimation, Probability

    Mixed · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    U

    University of Michigan

    Linear Regression Modeling for Health Data

    Skills you'll gain: Statistical Modeling, Regression Analysis, Statistical Inference, Probability & Statistics, Correlation Analysis, Data Analysis, Statistical Analysis, Statistical Hypothesis Testing, R Programming, Predictive Modeling

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
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    I

    Imperial College London

    Logistic Regression in R for Public Health

    Skills you'll gain: Descriptive Statistics, Exploratory Data Analysis, Regression Analysis, Statistics, R Programming, Predictive Modeling, Statistical Analysis, Feature Engineering, Probability & Statistics, Data Wrangling, Statistical Inference, R (Software), Data Cleansing, Public Health

    4.8
    Rating, 4.8 out of 5 stars
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    367 reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
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    Illinois Tech

    Variable Selection, Model Validation, Nonlinear Regression

    Skills you'll gain: Statistical Inference, Statistical Analysis, Regression Analysis, Statistical Modeling, R Programming, Predictive Modeling, Mathematical Modeling, Statistical Hypothesis Testing, Data Validation, Probability Distribution, Probability

    Build toward a degree

    4.6
    Rating, 4.6 out of 5 stars
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    7 reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
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    Illinois Tech

    Bayesian Computational Statistics

    Skills you'll gain: Bayesian Statistics, Data Analysis, Statistical Modeling, Statistical Software, Statistical Programming, Statistical Methods, Regression Analysis, Statistical Inference, R Programming, Numerical Analysis, Sampling (Statistics), Markov Model, Probability, Simulations, Probability Distribution

    Build toward a degree

    Intermediate · Course · 1 - 3 Months

  • Status: New
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    University of Pittsburgh

    Linear Algebra and Regression Fundamentals for Data Science

    Skills you'll gain: NumPy, Matplotlib, Linear Algebra, Pandas (Python Package), Data Manipulation, Applied Mathematics, Python Programming, Data Analysis, Data Science, Regression Analysis, Data Visualization Software, Mathematics and Mathematical Modeling, Probability & Statistics, Numerical Analysis, Mathematical Modeling, Machine Learning, Computational Logic, Logical Reasoning

    Build toward a degree

    Beginner · Course · 1 - 4 Weeks

  • Status: New
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    E

    EDUCBA

    Logistic Regression with SAS: Build & Evaluate Models

    Skills you'll gain: Feature Engineering, SAS (Software), Classification And Regression Tree (CART), Predictive Modeling, Statistical Modeling, Regression Analysis, Predictive Analytics, Applied Machine Learning, Statistical Methods, Data Processing, Data Manipulation, Data Cleansing, Data Transformation, Statistical Analysis, Exploratory Data Analysis

    Mixed · Course · 1 - 4 Weeks

  • Status: New
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    Simplilearn

    Linear Algebra for ML and Analytics Training

    Skills you'll gain: Mathematical Modeling, Linear Algebra, Dimensionality Reduction, Applied Mathematics, Data Analysis, Applied Machine Learning, Analytics, Data Science

    Beginner · Course · 1 - 4 Weeks

  • Status: Free Trial
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    J

    Johns Hopkins University

    Advanced Linear Models for Data Science 1: Least Squares

    Skills you'll gain: Regression Analysis, Statistical Modeling, R Programming, Linear Algebra, Data Science, Mathematical Modeling, Predictive Modeling, Statistics, Statistical Analysis, Applied Mathematics, Advanced Mathematics

    4.5
    Rating, 4.5 out of 5 stars
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    188 reviews

    Advanced · Course · 1 - 3 Months

  • Status: Free Trial
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    J

    Johns Hopkins University

    Quantifying Relationships with Regression Models

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

    4.6
    Rating, 4.6 out of 5 stars
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    23 reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
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    U

    University of California, Santa Cruz

    Bayesian Statistics: Time Series Analysis

    Skills you'll gain: Time Series Analysis and Forecasting, Forecasting, R Programming, Bayesian Statistics, Advanced Analytics, Statistical Modeling, R (Software), Statistical Analysis, Statistical Inference, Data Analysis, Mathematical Modeling, Probability Distribution

    4.2
    Rating, 4.2 out of 5 stars
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    17 reviews

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
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    W

    Wesleyan University

    Regression Modeling in Practice

    Skills you'll gain: Regression Analysis, Statistical Analysis, Statistical Modeling, Data Analysis, Correlation Analysis, SAS (Software), Scatter Plots, Statistical Programming, Predictive Modeling, Statistical Hypothesis Testing, Plot (Graphics), Python Programming

    4.4
    Rating, 4.4 out of 5 stars
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    274 reviews

    Mixed · Course · 1 - 4 Weeks

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In summary, here are 10 of our most popular bayesian linear regression courses

  • Logistic Regression Fundamentals: Analyze & Predict: EDUCBA
  • Linear Regression Modeling for Health Data: University of Michigan
  • Logistic Regression in R for Public Health: Imperial College London
  • Variable Selection, Model Validation, Nonlinear Regression: Illinois Tech
  • Bayesian Computational Statistics: Illinois Tech
  • Linear Algebra and Regression Fundamentals for Data Science: University of Pittsburgh
  • Logistic Regression with SAS: Build & Evaluate Models: EDUCBA
  • Linear Algebra for ML and Analytics Training: Simplilearn
  • Advanced Linear Models for Data Science 1: Least Squares: Johns Hopkins University
  • Quantifying Relationships with Regression Models: Johns Hopkins University

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