Introduction to PyMC3 - Part 1-Introduction to PyMC3
Welcome to Course 3!
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What can you expect from this course/specialization?
Probabilistic Programming with PyMC3
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Probabilistic Programming Frameworks
An introduction to PyMC3
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Inference with PyMC3
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Composition of Distributions
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HPD, HDI and ROPE
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Credible and Confidence Intervals
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Plate Notation
Introduction to PyMC3 - Part 1-Inferring Distributions with PyMC3
Modeling with a Gaussian Distribution
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Posterior Predictive Checks
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Robust Models
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Hierarchical Models
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Shrinkage in Hierarchical Models
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Introduction to PyMC3 - Part 2-Regression
Linear Regression
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Mean-centering for Linear Regression
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Robust Linear Regression
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Hierarchical Linear Regression
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Polynomial Linear Regression
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Multiple Linear Regression
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Introduction to PyMC3 - Part 2-Classification
Logistic Regression
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Logistic Regression with PyMC3
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Decision Boundary for Classification
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Multiple Logistic Regression
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Multiclass Logistic Regression
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Case Study with PyMC3 - I
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Case Study with PyMC3 - II
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Case Study with PyMC3 - III
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Metrics in PyMC3-Introduction to metrics
Introduction to Metrics and Tuning
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Metropolis and HMC
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Mixing and Potential Scale Reduction Factor
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Centered and Non-centered Parameterization
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Assess convergence in PyMC3
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Forest plots for visualization
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Autocorrelation and Effective Sample Size
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Monte Carlo error and Divergences
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Visualization in Bayesian Workflow
Tuning
Improved Rhat
Metrics in PyMC3-Metrics in PyMC3
Diagnosing issues in PyMC3
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Diagnosing issues in PyMC3 with the multiclass classification problem
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Debugging in PyMC3
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