Bring back learn page. (#5833)

* Bring back learning page.

* Remove no-sidebar.

* Updates to user guide.

* Remove learn.md.

* Add link to PyMC Labs.

* Link to correct image.

* Improve cosulting page. Rename to learn.

* Change cards to use Oriol's proposed format.

* fix sphinx build

* add newline at end of file

* ensure img kwarg is in the next line of directive definition

Co-authored-by: Oriol Abril-Pla <[email protected]>

Author: twiecki

docs/source/api.rst

@@ -1,8 +1,8 @@
 .. _api:
 
-*************
-API Reference
-*************
+***
+API
+***
 
 .. toctree::
    :maxdepth: 1

docs/source/conf.py

@@ -154,7 +154,7 @@
 myst_heading_anchors = None
 
 rediraffe_redirects = {
-    "index.md": "learning.md",
+    "index.md": "learn.md",
 }
 # The reST default role (used for this markup: `text`) to use for all
 # documents.
@@ -309,7 +309,9 @@ def setup(app):
 # html_use_smartypants = True
 
 # Custom sidebar templates, maps document names to template names.
-html_sidebars = {"**": ["sidebar-nav-bs.html"]}
+html_sidebars = {
+    "**": ["sidebar-nav-bs.html"],
+}
 
 # Additional templates that should be rendered to pages, maps page names to
 # template names.

docs/source/index.md

@@ -9,7 +9,7 @@ sd_hide_title: true
 
 Home <https://www.pymc.io/welcome.html>
 Examples <https://www.pymc.io/projects/examples/en/latest/gallery.html>
-learning
+Learn <learn>
 api
 Community <https://www.pymc.io/community/index.html>
 contributing/index

docs/source/learn.md

@@ -0,0 +1,32 @@
+(learn)=
+# Learn PyMC & Bayesian modeling
+
+:::{toctree}
+:maxdepth: 1
+installation
+learn/core_notebooks/index
+learn/books
+learn/videos_and_podcasts
+learn/consulting
+glossary
+:::
+
+## At a glance
+### Beginner
+  - Book: [Bayesian Methods for Hackers](https://github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers)
+  - Book: [Bayesian Analysis with Python](https://www.packtpub.com/big-data-and-business-intelligence/bayesian-analysis-python-second-edition)
+
+### Intermediate
+  - {ref}`pymc_overview` shows PyMC 4.0 code in action
+  - Example notebooks: {ref}`nb:index`
+    - {ref}`GLM_linear`
+    - {ref}`posterior_predictive`
+    - Comparing models: {ref}`model_comparison`
+    - Shapes and dimensionality {ref}`dimensionality`
+  - {ref}`videos_and_podcasts`
+  - Book: [Bayesian Modeling and Computation in Python](https://bayesiancomputationbook.com/welcome.html)
+
+### Advanced
+  - {octicon}`plug;1em;sd-text-info` Experimental and cutting edge functionality: {doc}`pmx:index` library
+  - {octicon}`gear;1em;sd-text-info` PyMC internals guides (To be outlined and referenced here once [pymc#5538](https://github.com/pymc-devs/pymc/issues/5538)
+is addressed)

docs/source/learn/books.md

@@ -1,8 +1,11 @@
 (books)=
 # Books
+:::::{container} full-width
+::::{grid} 1 2 2 3
+:gutter: 3
 
-## Bayesian Methods for Hackers
-
+:::{grid-item-card} Bayesian Methods for Hackers
+:img-top: https://camo.githubusercontent.com/4a0aca82ca82efab71747d00db30f3a68de98e82/687474703a2f2f692e696d6775722e636f6d2f36444b596250622e706e673f31
 By Cameron Davidson-Pilon
 
 The "hacker" in the title  means learn-as-you-code. This hands-on introduction teaches intuitive definitions of the Bayesian approach to statistics, worklflow and decision-making by applying them using PyMC.
@@ -11,30 +14,37 @@ The "hacker" in the title  means learn-as-you-code. This hands-on introduction t
 
 [Project homepage](http://camdavidsonpilon.github.io/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/)
 
-## Bayesian Analysis with Python
+:::
+
+:::{grid-item-card} Bayesian Analysis with Python
+:img-top: https://raw.githubusercontent.com/aloctavodia/BAP/master/Cover.png
 
 By Osvaldo Martin
 
+
 A great introductory book written by a maintainer of PyMC. It provides a hands-on introduction to the main concepts of Bayesian statistics using synthetic and real data sets. Mastering the concepts in this book is a great foundation to pursue more advanced knowledge.
 
 [Book website](https://www.packtpub.com/big-data-and-business-intelligence/bayesian-analysis-python-second-edition)
 
 [Code and errata in PyMC 3.x](https://github.com/aloctavodia/BAP)
+:::
 
-## Doing Bayesian Data Analysis
+:::{grid-item-card} Doing Bayesian Data Analysis
+:img-top: https://jkkweb.sitehost.iu.edu/DoingBayesianDataAnalysis/DBDA2Ecover.png
 
 By John K. Kruschke
 
-Principled introduction to Bayesian data analysis, with practical exercises. The book's original examples are coded in R, but notebooks with a PyMC port of the code are available through the links below.
 
+Principled introduction to Bayesian data analysis, with practical exercises. The book's original examples are coded in R, but notebooks with a PyMC port of the code are available through the links below.
 
 [Book website](https://sites.google.com/site/doingbayesiandataanalysis/home)
 
-[PyMC 3.x port of the first edition's code](https://github.com/aloctavodia/Doing_bayesian_data_analysis)
-
 [PyMC 3.x port of the second edition's code](https://github.com/JWarmenhoven/DBDA-python)
 
-## Statistical Rethinking
+:::
+
+:::{grid-item-card} Statistical Rethinking
+:img-top: http://xcelab.net/rm/wp-content/uploads/2012/01/9781482253443-191x300.jpg
 
 By Richard McElreath
 
@@ -44,16 +54,21 @@ A Bayesian Course with Examples in R and Stan.
 
 [PyMC 3.x port of the code](https://github.com/pymc-devs/resources/tree/master/Rethinking)
 
-## Bayesian Modeling and Computation in Python
+:::
+
+:::{grid-item-card} Bayesian Modeling and Computation in Python
+:img-top: https://bayesiancomputationbook.com/_images/Cover.jpg
 
 By Osvaldo Martin, Ravin Kumar and Junpeng Lao
 
-Bayesian Modeling and Computation in Python aims to help beginner Bayesian practitioners to become intermediate modelers. It uses a hands on approach with PyMC and ArviZ focusing on the practice of applied statistics with references to the underlying mathematical theory.
+Hands on approach with PyMC and ArviZ focusing on the practice of applied statistics.
 
-[Book website](https://bayesiancomputationbook.com/welcome.html)
-(the book website contains the whole book, code examples, and notebook in online format)
+[Website + code](https://bayesiancomputationbook.com/welcome.html)
 
-## Bayesian Cognitive Modeling: A Practical Course
+:::
+
+:::{grid-item-card} Bayesian Cognitive Modeling: A Practical Course
+:img-top: https://images-na.ssl-images-amazon.com/images/I/51K33XI2I8L._SX330_BO1,204,203,200_.jpg
 
 By Michael Lee and Eric-Jan Wagenmakers
 
@@ -62,8 +77,10 @@ Focused on using Bayesian statistics in cognitive modeling.
 [Book website](https://bayesmodels.com/)
 
 [PyMC 3.x implementations](https://github.com/pymc-devs/resources/tree/master/BCM)
+:::
 
-## Bayesian Data Analysis
+:::{grid-item-card} Bayesian Data Analysis
+:img-top: http://www.stat.columbia.edu/~gelman/book/bda_cover.png
 
 By Andrew Gelman, John Carlin, Hal Stern, David Dunson, Aki Vehtari, and Donald Rubin
 
@@ -72,3 +89,6 @@ A comprehensive, standard, and wonderful textbook on Bayesian methods.
 [Book website](https://www.stat.columbia.edu/~gelman/book/)
 
 [Examples and exercises implemented in PyMC 3.x](https://github.com/pymc-devs/resources/tree/master/BDA3)
+
+::::
+:::::

docs/source/learn/consulting.md

@@ -0,0 +1,13 @@
+(consulting)=
+# Consulting
+
+<center><a href="https://www.pymc-labs.io/"><img src="https://github.com/pymc-labs/brand/blob/main/logos/4-pymc-labs-transp-black.png?raw=true" class="center" width="75%"></a></center>
+<br>
+
+If you need professional help with your PyMC model, [PyMC Labs](https://www.pymc-labs.io) is a Bayesian consultancy consisting of [members of the PyMC core development team](https://www.pymc-labs.io/team/). Work we typically do includes:
+* Model speed-ups (reparameterizations, JAX, [GPU sampling](https://www.pymc-labs.io/blog-posts/pymc-stan-benchmark/))
+* Improving models (adding hierarchy, time-series structure etc)
+* Building new models to solve applied business problems
+* [Bayesian Media Mix Models](https://www.pymc-labs.io/blog-posts/bayesian-media-mix-modeling-for-marketing-optimization/) for marketing attribution
+
+Interested? Send us an email at [[email protected]](mailto:[email protected]).

docs/source/learn/videos_and_podcasts.md

@@ -11,6 +11,16 @@
 Actively curated [YouTube playlist](https://www.youtube.com/playlist?list=PL1Ma_1DBbE82OVW8Fz_6Ts1oOeyOAiovy) of PyMC talks
 :::
 
+:::{card} PyMC Labs Youtube channel
+
+[See all videos here](https://www.youtube.com/c/PyMCLabs/videos)
+:::
+
+:::{card} PyMCon 2020 talks
+
+[See all videos here](https://www.youtube.com/playlist?list=PLD1x-BW9UdeG68AQj6rDRfGiFFrpZ3cgu)
+:::
+
 :::{card} Learning Bayesian Statistics podcast
 
 [See all videos here](https://www.youtube.com/channel/UCAwVseuhVrpJFfik_cMHrhQ/videos)