Introductory Course
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Welcome
Welcome to Intuitive Bayes
Course Welcome and Orientation
Github Repository and Code Access
Intuitive Bayes Discourse Community
Course Presurvey
Optional Orientation: Github
Optional Orientation: Discourse
Optional Orientation: Podia
About this course
Why We Created This
What is Different About This Course
Who is This Course For
Playmobil vs Lego
Comparison to Other Approaches
When Does Bayes Work Best
Real World Applications
Prerequisites and Outline
Lesson Summary
Lesson References
Lesson Feedback Form
How It All Fits Together
Lesson Introduction
Considering Multiple Solutions
Statistics just becomes counting
Inside the Magic Machine
The Magic of Sampling
Doing it in Code
Lesson Summary
Lesson References
Lesson Exercises
Beta Lesson Feedback Form
AB Testing Hands On
Lesson Introduction
Installing PyMC
Setting Up The Model
Getting the Plausible Values
Getting Analytical
Putting it All Together
Lesson Summary
Lesson References
Lesson Exercises
Lesson Feedback Form
Computational Distributions
Lesson Introduction
Distributions and Uncertainty
Distribution Inputs: Parameters
Distribution Outputs: PMF/PDF
Two Types of Samples
Two Types of Spaces
Lesson Recap
Lesson References
Lesson Exercises
Lesson Feedback Form
Bayes Rule
Lesson Introduction
Prior Distribution
Likelihood Distribution
Posterior Distribution
Prior and Posterior Predictive Distributions
Markov Chain Monte Carlo
Common Distributions in Modern Bayes
Lesson Recap
Lesson References
Lesson Exercises
Lesson Feedback Form
Bayesian Linear Regression
Lesson Introduction
The Setting
Exploring the data -- and why it matters
Visual Exploratory Analysis
A Non-Bayesian Linear Regression
A Simple PyMC model
Adding Predictors to our Model
Predicting Out-of-Sample
From Predictions to Business Insights
The Bayesian Workflow
Lesson Summary
Lesson References
Lesson Exercises
Lesson Feedback Form
Hierarchical Linear Regression
Lesson Introduction
Motivation for Hierarchical models
Distributions Over Parameters
Hierarchical Models
Effect of Hierarchy
Power of Bayes
Lesson References
Lesson Exercises
Lesson Feedback Form
The next steps in your Bayesian exploration
Continuing your journey after this cousre
Post Course Feedback
testimonials-proper.mov
Products
Course
Section
The next steps in your Bayesian exploration
The next steps in your Bayesian exploration
Introductory Course
Buy now
Learn more
Welcome
Welcome to Intuitive Bayes
Course Welcome and Orientation
Github Repository and Code Access
Intuitive Bayes Discourse Community
Course Presurvey
Optional Orientation: Github
Optional Orientation: Discourse
Optional Orientation: Podia
About this course
Why We Created This
What is Different About This Course
Who is This Course For
Playmobil vs Lego
Comparison to Other Approaches
When Does Bayes Work Best
Real World Applications
Prerequisites and Outline
Lesson Summary
Lesson References
Lesson Feedback Form
How It All Fits Together
Lesson Introduction
Considering Multiple Solutions
Statistics just becomes counting
Inside the Magic Machine
The Magic of Sampling
Doing it in Code
Lesson Summary
Lesson References
Lesson Exercises
Beta Lesson Feedback Form
AB Testing Hands On
Lesson Introduction
Installing PyMC
Setting Up The Model
Getting the Plausible Values
Getting Analytical
Putting it All Together
Lesson Summary
Lesson References
Lesson Exercises
Lesson Feedback Form
Computational Distributions
Lesson Introduction
Distributions and Uncertainty
Distribution Inputs: Parameters
Distribution Outputs: PMF/PDF
Two Types of Samples
Two Types of Spaces
Lesson Recap
Lesson References
Lesson Exercises
Lesson Feedback Form
Bayes Rule
Lesson Introduction
Prior Distribution
Likelihood Distribution
Posterior Distribution
Prior and Posterior Predictive Distributions
Markov Chain Monte Carlo
Common Distributions in Modern Bayes
Lesson Recap
Lesson References
Lesson Exercises
Lesson Feedback Form
Bayesian Linear Regression
Lesson Introduction
The Setting
Exploring the data -- and why it matters
Visual Exploratory Analysis
A Non-Bayesian Linear Regression
A Simple PyMC model
Adding Predictors to our Model
Predicting Out-of-Sample
From Predictions to Business Insights
The Bayesian Workflow
Lesson Summary
Lesson References
Lesson Exercises
Lesson Feedback Form
Hierarchical Linear Regression
Lesson Introduction
Motivation for Hierarchical models
Distributions Over Parameters
Hierarchical Models
Effect of Hierarchy
Power of Bayes
Lesson References
Lesson Exercises
Lesson Feedback Form
The next steps in your Bayesian exploration
Continuing your journey after this cousre
Post Course Feedback
testimonials-proper.mov
Where to go from here if you'd like to keep learning
3 Lessons
Continuing your journey after this cousre
Post Course Feedback
testimonials-proper.mov