diff --git a/config.toml b/config.toml
index f2b02f1d8..4014e9ceb 100644
--- a/config.toml
+++ b/config.toml
@@ -15,6 +15,7 @@ enableEmoji = true
[permalinks]
blog = "/:slug/"
+ bookshelf = "/:slug/"
[params]
diff --git a/content/bookshelf/2019-01-06-an-introduction-to-statistical-learning/index.fr 2.md b/content/bookshelf/2019-01-06-an-introduction-to-statistical-learning/index.fr 2.md
deleted file mode 100644
index 93dd2e7c0..000000000
--- a/content/bookshelf/2019-01-06-an-introduction-to-statistical-learning/index.fr 2.md
+++ /dev/null
@@ -1,55 +0,0 @@
----
-title: "Book Review: An Introduction to Statistical Learning"
-slug: islr
-author: "Christopher Blier-Wong"
-description: "Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani"
-date: '2019-01-06'
-type: "book review"
-tags:
-- Machine Learning
-- Statistics
-- Textbook
-- R
-output:
- html_document:
- keep_md: true
----
-
- > Ranking: :star: :star: :star: :star: :star:
-
- > Coding prerequisites : low
-
- > Math/stats prerequisites : low
-
- > Level : easy
-
-
-# Summary
-
-This book is mostly interested in supervised learning, the task of
-using statistical models to predict the relationship between
-predictors and a response. Given there is a function $f$ that
-provides a relationship between explanatory variables $X$ and a
-response variable $Y$, what are statistical methods for estimating
-$f$.
-
-# Review
-
-There are two steps in the education of a data scientist :
-understanding statistical models, and putting them in practice.
-This book definitely helps on the practice part, assuming little
-mathematical or statistical knowledge from the reader. This book
-is a great companion to it's big brother, The Elements of Statistical
-Learning. First of all, R is a great language to start with
-statistical learning as it's really easy to manipulate data.
-
-Exercices are simple but labs are great for understanding and as a
-way to
-
-I particularly liked their chapter 5, treating resampling methods.
-Most of us know what $k$-fold cross validation is, but how and why
-it works isn't understood by all. This chapter helps us understand
-the bias-variance tradeoff for the choice of $k$ in the method. This
-is an example of a situation does not only show the method, but
-also examines their statistical properties, something not all machine
-learning books do.
diff --git a/content/bookshelf/2019-01-06-an-introduction-to-statistical-learning/index.fr.md b/content/bookshelf/2019-01-06-an-introduction-to-statistical-learning/index.fr.md
deleted file mode 100644
index 93dd2e7c0..000000000
--- a/content/bookshelf/2019-01-06-an-introduction-to-statistical-learning/index.fr.md
+++ /dev/null
@@ -1,55 +0,0 @@
----
-title: "Book Review: An Introduction to Statistical Learning"
-slug: islr
-author: "Christopher Blier-Wong"
-description: "Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani"
-date: '2019-01-06'
-type: "book review"
-tags:
-- Machine Learning
-- Statistics
-- Textbook
-- R
-output:
- html_document:
- keep_md: true
----
-
- > Ranking: :star: :star: :star: :star: :star:
-
- > Coding prerequisites : low
-
- > Math/stats prerequisites : low
-
- > Level : easy
-
-
-# Summary
-
-This book is mostly interested in supervised learning, the task of
-using statistical models to predict the relationship between
-predictors and a response. Given there is a function $f$ that
-provides a relationship between explanatory variables $X$ and a
-response variable $Y$, what are statistical methods for estimating
-$f$.
-
-# Review
-
-There are two steps in the education of a data scientist :
-understanding statistical models, and putting them in practice.
-This book definitely helps on the practice part, assuming little
-mathematical or statistical knowledge from the reader. This book
-is a great companion to it's big brother, The Elements of Statistical
-Learning. First of all, R is a great language to start with
-statistical learning as it's really easy to manipulate data.
-
-Exercices are simple but labs are great for understanding and as a
-way to
-
-I particularly liked their chapter 5, treating resampling methods.
-Most of us know what $k$-fold cross validation is, but how and why
-it works isn't understood by all. This chapter helps us understand
-the bias-variance tradeoff for the choice of $k$ in the method. This
-is an example of a situation does not only show the method, but
-also examines their statistical properties, something not all machine
-learning books do.
diff --git a/content/bookshelf/2021-03-09-an-example/index.en.md b/content/bookshelf/2021-03-09-an-example/index.en.md
new file mode 100644
index 000000000..ddb4a6f18
--- /dev/null
+++ b/content/bookshelf/2021-03-09-an-example/index.en.md
@@ -0,0 +1,26 @@
+---
+title: 'Book Review: An Example'
+author: 'David Beauchemin and Annie Deshaies'
+description: 'Jon Doe and Jone Doe'
+date: '2021-03-09'
+type: 'bookshelf'
+tags: ['Machine Learning', 'tags2', 'tags3', 'Python']
+slug: example
+summary: 'This book review is an example for others to do a book review.'
+---
+
+**Ranking**: :star: :star: :star: :star: :star:
+
+**Coding prerequisites**: low
+
+**Math/stats prerequisites**: low
+
+**Level**: easy
+
+# Summary
+
+This book review is an example for others to do a book review.
+
+# Review
+
+Here we would write down the review of the book. Talking about what we liked, what we did not like and other interesting stuff.
\ No newline at end of file
diff --git a/content/bookshelf/2021-03-09-an-example/index.fr.md b/content/bookshelf/2021-03-09-an-example/index.fr.md
new file mode 100644
index 000000000..33d265778
--- /dev/null
+++ b/content/bookshelf/2021-03-09-an-example/index.fr.md
@@ -0,0 +1,26 @@
+---
+title: 'Critique de livres : Un exemple'
+author: 'David Beauchemin et Annie Deshaies'
+description: 'Jon Doe et Jone Doe'
+date: '2021-03-09'
+type: 'bookshelf'
+tags: ['apprentissage automatique', 'tags2', 'tags3', 'Python']
+slug: exemple
+summary: 'Cette critique de livre est un exemple pour d'autres de faire une critique de livre.'
+---
+
+**Appréciation** : :star : :star : :star : :star : :star :
+
+**Niveau de difficulté de programmation** : faible
+
+**Prérequis maths/statistiques** : faible
+
+**Niveau** : facile
+
+# Résumé
+
+Cette critique de livre est un exemple pour d'autres de faire une critique de livre.
+
+# Critique
+
+Ici, on écrirait la critique du livre. Nous pourrions parler de ce que nous avons aimé, de ce que nous n'avons pas aimé et d'autres choses intéressantes.
\ No newline at end of file
diff --git a/content/bookshelf/_index.en.md b/content/bookshelf/_index.en.md
index f91efe584..399ffd8b2 100644
--- a/content/bookshelf/_index.en.md
+++ b/content/bookshelf/_index.en.md
@@ -2,4 +2,4 @@
title = "Bookshelf"
type = "book review"
date = "2020-01-03"
-+++
\ No newline at end of file
++++
diff --git a/content/test/2019-01-06-an-introduction-to-statistical-learning/index.en.md b/content/test/2019-01-06-an-introduction-to-statistical-learning/index.en.md
new file mode 100644
index 000000000..f3ceec18e
--- /dev/null
+++ b/content/test/2019-01-06-an-introduction-to-statistical-learning/index.en.md
@@ -0,0 +1,53 @@
+---
+title: 'Book Review: An Introduction to Statistical Learning'
+author: 'Christopher Blier-Wong'
+description: 'Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani'
+date: '2019-01-06'
+type: 'bookshelf'
+tags: ['Machine Learning', 'Statistics', 'Textbook', 'R']
+slug: islr
+summary: 'This book is mostly interested in supervised learning, the task of
+using statistical models to predict the relationship between
+predictors and a response. Given there is a function $f$ that
+provides a relationship between explanatory variables $X$ and a
+response variable $Y$, what are statistical methods for estimating
+$f$.'
+---
+
+**Ranking**: :star: :star: :star: :star: :star:
+
+**Coding prerequisites**: low
+
+**Math/stats prerequisites**: low
+
+**Level**: easy
+
+# Summary
+
+This book is mostly interested in supervised learning, the task of
+using statistical models to predict the relationship between
+predictors and a response. Given there is a function $f$ that
+provides a relationship between explanatory variables $X$ and a
+response variable $Y$, what are statistical methods for estimating
+$f$.
+
+# Review
+
+There are two steps in the education of a data scientist :
+understanding statistical models, and putting them in practice.
+This book definitely helps on the practice part, assuming little
+mathematical or statistical knowledge from the reader. This book
+is a great companion to it's big brother, The Elements of Statistical
+Learning. First of all, R is a great language to start with
+statistical learning as it's really easy to manipulate data.
+
+Exercices are simple but labs are great for understanding and as a
+way to
+
+I particularly liked their chapter 5, treating resampling methods.
+Most of us know what $k$-fold cross validation is, but how and why
+it works isn't understood by all. This chapter helps us understand
+the bias-variance tradeoff for the choice of $k$ in the method. This
+is an example of a situation does not only show the method, but
+also examines their statistical properties, something not all machine
+learning books do.
diff --git a/content/test/2019-01-06-an-introduction-to-statistical-learning/index.fr.md b/content/test/2019-01-06-an-introduction-to-statistical-learning/index.fr.md
new file mode 100644
index 000000000..33d265778
--- /dev/null
+++ b/content/test/2019-01-06-an-introduction-to-statistical-learning/index.fr.md
@@ -0,0 +1,26 @@
+---
+title: 'Critique de livres : Un exemple'
+author: 'David Beauchemin et Annie Deshaies'
+description: 'Jon Doe et Jone Doe'
+date: '2021-03-09'
+type: 'bookshelf'
+tags: ['apprentissage automatique', 'tags2', 'tags3', 'Python']
+slug: exemple
+summary: 'Cette critique de livre est un exemple pour d'autres de faire une critique de livre.'
+---
+
+**Appréciation** : :star : :star : :star : :star : :star :
+
+**Niveau de difficulté de programmation** : faible
+
+**Prérequis maths/statistiques** : faible
+
+**Niveau** : facile
+
+# Résumé
+
+Cette critique de livre est un exemple pour d'autres de faire une critique de livre.
+
+# Critique
+
+Ici, on écrirait la critique du livre. Nous pourrions parler de ce que nous avons aimé, de ce que nous n'avons pas aimé et d'autres choses intéressantes.
\ No newline at end of file
diff --git a/layouts/book/content-list.html b/layouts/book/content-list.html
deleted file mode 100644
index 634e7dda7..000000000
--- a/layouts/book/content-list.html
+++ /dev/null
@@ -1,13 +0,0 @@
-
- {{ .Render "header" }}
- {{ .Render "featured" }}
- {{ $.Scratch.Set "summary" ((delimit (findRE "(.|\n)*?" .Content 1) "") | truncate (default 500 .Site.Params.summary_length) (default "…" .Site.Params.text.truncated ) | replaceRE "&" "&" | safeHTML) }}
- {{ $.Scratch.Get "summary" }}
-
-
-
\ No newline at end of file
diff --git a/layouts/book/header.html b/layouts/book/header.html
deleted file mode 100644
index a941f0909..000000000
--- a/layouts/book/header.html
+++ /dev/null
@@ -1,31 +0,0 @@
-
-