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Add Example Gallery (#1611)
* This is a combination of 3 commits. init fix galery layout lower case * generate images on the go * This is a combination of 5 commits. delete images from repo try fix error try gix error try fix error update git ignore * re add images * undo file removal * try rm images again * rm extra req * better name * rtd reqs * rtd reqs * rtd reqs * undo * undo makefile * feedback * rm how to
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‎.gitignore‎

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# PyCharm .idea files
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.idea/
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# Gallery images
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docs/source/gallery/images/

‎.readthedocs.yml‎

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version: 2
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sphinx:
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configuration: docs/source/conf.py
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configuration: docs/source/conf.py
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build:
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os: ubuntu-22.04
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tools:
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python: "3.10"
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jobs:
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pre_build:
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# Install core dependencies first
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- pip install --upgrade pip setuptools wheel
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- python scripts/generate_gallery.py
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python:
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install:
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- method: pip
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path: .
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extra_requirements:
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- docs
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install:
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- method: pip
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path: .
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extra_requirements:
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- docs

‎Makefile‎

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html: ## Install documentation dependencies and build HTML docs
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pip install .[docs]
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python scripts/generate_gallery.py
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sphinx-build docs/source docs/build -b html
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cleandocs: ## Clean the documentation build directories

‎docs/source/gallery/README.md‎

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# PyMC-Marketing Example Gallery
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This directory contains the gallery view for the PyMC-Marketing example notebooks.
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## Gallery Structure
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The gallery displays thumbnails and links to all example notebooks, organized by category.
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## Adding New Examples to the Gallery
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When adding new example notebooks:
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1. Add the notebook to the appropriate directory in `docs/source/notebooks/`
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2. Update the gallery entry in `gallery.md`
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3. Create a thumbnail image for the notebook (ideally a screenshot of a key visualization from the notebook) and place it in the `images/` directory
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4. Run `python create_gallery_images.py` to generate a placeholder thumbnail if you don't have a specific image
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## Gallery Images
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The gallery uses thumbnail images to provide visual navigation. For best results:
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- Images should be in PNG format
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- Images should have a 4:3 aspect ratio
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- Size should be approximately 600x450 pixels
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- Names should match the notebook filename
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## Updating the Gallery
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The gallery is structured using the Sphinx Design extension's grid layout. See the [Sphinx Design documentation](https://sphinx-design.readthedocs.io/en/latest/grids.html) for more information on customizing the grid layout.

‎docs/source/gallery/gallery.md‎

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(gallery)=
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# Example Gallery
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```{toctree}
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:hidden:
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```
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## Introduction
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Welcome to the PyMC-Marketing example gallery! This gallery provides visual navigation to all of our example notebooks to help you quickly find the techniques and models relevant to your marketing analytics needs.
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## Marketing Mix Models (MMM)
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### Fundamentals
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::::{grid} 1 2 3 3
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:gutter: 3
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:::{grid-item-card} MMM Example Notebook
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:img-top: ../gallery/images/mmm_example.png
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:link: ../notebooks/mmm/mmm_example.html
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:::
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:::{grid-item-card} Custom Models with MMM components
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:img-top: ../gallery/images/mmm_components.png
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:link: ../notebooks/mmm/mmm_components.html
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:::
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:::{grid-item-card} MMM Multidimensional Example Notebook (e.g. Geo-MMM)
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:img-top: ../gallery/images/mmm_multidimensional_example.png
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:link: ../notebooks/mmm/mmm_multidimensional_example.html
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:::
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::::
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### Budget Allocation
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::::{grid} 1 2 3 3
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:gutter: 3
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:::{grid-item-card} Budget Allocation Example
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:img-top: ../gallery/images/mmm_budget_allocation_example.png
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:link: ../notebooks/mmm/mmm_budget_allocation_example.html
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:::
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:::{grid-item-card} Budget Allocation Risk Assessment
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:img-top: ../gallery/images/mmm_allocation_assessment.png
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:link: ../notebooks/mmm/mmm_allocation_assessment.html
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:::
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::::
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### Lift Test Calibration
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::::{grid} 1 2 3 3
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:gutter: 3
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:::{grid-item-card} Lift Test Analysis
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:img-top: ../gallery/images/mmm_lift_test.png
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:link: ../notebooks/mmm/mmm_lift_test.html
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:::
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:::{grid-item-card} Case Study: Unobserved Confounders, ROAS and Lift Tests
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:img-top: ../gallery/images/mmm_roas.png
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:link: ../notebooks/mmm/mmm_roas.html
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:::
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::::
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### Time-Varying Parameters
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::::{grid} 1 2 3 3
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:gutter: 3
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:::{grid-item-card} MMM with time-varying parameters
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:img-top: ../gallery/images/mmm_tvp_example.png
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:link: ../notebooks/mmm/mmm_tvp_example.html
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:::
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:::{grid-item-card} MMM with time-varying media baseline
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:img-top: ../gallery/images/mmm_time_varying_media_example.png
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:link: ../notebooks/mmm/mmm_time_varying_media_example.html
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:::
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::::
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### Model Evaluation
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::::{grid} 1 2 3 3
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:gutter: 3
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:::{grid-item-card} Cross-Validation
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:img-top: ../gallery/images/mmm_time_slice_cross_validation.png
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:link: ../notebooks/mmm/mmm_time_slice_cross_validation.html
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:::
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:::{grid-item-card} Model Evaluation
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:img-top: ../gallery/images/mmm_evaluation.png
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:link: ../notebooks/mmm/mmm_evaluation.html
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:::
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::::
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### Causal Inference
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::::{grid} 1 2 3 3
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:gutter: 3
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:::{grid-item-card} Causal Identification
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:img-top: ../gallery/images/mmm_causal_identification.png
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:link: ../notebooks/mmm/mmm_causal_identification.html
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:::
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:::{grid-item-card} MMMs and Pearl's ladder of causal inference
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:img-top: ../gallery/images/mmm_counterfactuals.png
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:link: ../notebooks/mmm/mmm_counterfactuals.html
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:::
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::::
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### Case Studies
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::::{grid} 1 2 3 3
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:gutter: 3
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:::{grid-item-card} MMM Case Study
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:img-top: ../gallery/images/mmm_case_study.png
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:link: ../notebooks/mmm/mmm_case_study.html
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:::
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::::
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## Customer Lifetime Value (CLV) Models
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::::{grid} 1 2 3 3
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:gutter: 3
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:::{grid-item-card} CLV Quickstart
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:img-top: ../gallery/images/clv_quickstart.png
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:link: ../notebooks/clv/clv_quickstart.html
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:::
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:::{grid-item-card} BG/NBD Model
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:img-top: ../gallery/images/bg_nbd.png
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:link: ../notebooks/clv/bg_nbd.html
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:::
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:::{grid-item-card} MBG/NBD Model
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:img-top: ../gallery/images/mbg_nbd.png
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:link: ../notebooks/clv/mbg_nbd.html
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:::
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:::{grid-item-card} Pareto/NBD Model
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:img-top: ../gallery/images/pareto_nbd.png
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:link: ../notebooks/clv/pareto_nbd.html
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:::
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:::{grid-item-card} Gamma-Gamma Model
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:img-top: ../gallery/images/gamma_gamma.png
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:link: ../notebooks/clv/gamma_gamma.html
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:::
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:::{grid-item-card} sBG Model
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:img-top: ../gallery/images/sBG.png
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:link: ../notebooks/clv/sBG.html
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:::
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::::
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## Customer Choice Models
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::::{grid} 1 2 3 3
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:gutter: 3
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:::{grid-item-card} MV-ITS Saturated
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:img-top: ../gallery/images/mv_its_saturated.png
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:link: ../notebooks/customer_choice/mv_its_saturated.html
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:::
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:::{grid-item-card} MV-ITS Unsaturated
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:img-top: ../gallery/images/mv_its_unsaturated.png
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:link: ../notebooks/customer_choice/mv_its_unsaturated.html
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:::
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::::
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## General Tutorials
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::::{grid} 1 2 3 3
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:gutter: 3
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:::{grid-item-card} Model Configuration
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:img-top: ../gallery/images/model_configuration.png
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:link: ../notebooks/general/model_configuration.html
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:::
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:::{grid-item-card} Prior Predictive Checks
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:img-top: ../gallery/images/prior_predictive.png
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:link: ../notebooks/general/prior_predictive.html
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:::
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:::{grid-item-card} NUTS Samplers
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:img-top: ../gallery/images/other_nuts_samplers.png
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:link: ../notebooks/general/other_nuts_samplers.html
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:::
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::::

‎docs/source/getting_started/quickstart/clv/index.md‎

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Once fitted, we can use the model to predict the number of future purchases for known customers, the probability that they are still alive, and get various visualizations plotted.
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See the {ref}`howto` section for more on this.
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See the {ref}`gallery` section for more on this.

‎docs/source/getting_started/quickstart/customer_choice/index.md‎

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See the {ref}`howto` section for more information about using the customer choice module.
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See the {ref}`gallery` section for more information about using the customer choice module.

‎docs/source/index.md‎

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## Quick links
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:::::{grid} 1 1 2 2
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::::{grid-item-card} Example Gallery
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:class-header: sd-text-center no-border
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:class-title: sd-text-center
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:class-footer: no-border
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{material-outlined}`photo_library;5em`
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^^^^^^^^^^^^^^^
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Browse our visual gallery of example notebooks to quickly
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find the techniques and models relevant to your
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marketing analytics needs.
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:::{button-ref} gallery/gallery
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:expand:
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:color: secondary
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:ref-type: doc
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To the example gallery
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:::
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## Bayesian Marketing Mix Modeling (MMM) in PyMC
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Leverage our Bayesian MMM API to tailor your marketing strategies effectively. Leveraging on top of the research article [Jin, Yuxue, et al. “Bayesian methods for media mix modeling with carryover and shape effects.” (2017)](https://research.google/pubs/pub46001/), and extending it by integrating the expertise from core PyMC developers, our API provides:
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Leverage our Bayesian MMM API to tailor your marketing strategies effectively. Leveraging on top of the research article [Jin, Yuxue, et al. "Bayesian methods for media mix modeling with carryover and shape effects." (2017)](https://research.google/pubs/pub46001/), and extending it by integrating the expertise from core PyMC developers, our API provides:
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| Feature | Benefit |
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| ------------------------------------------ | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
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gallery/gallery
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‎docs/source/notebooks/index.md‎

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