diff --git a/BHPD/01-DNN-Regression.ipynb b/BHPD/01-DNN-Regression.ipynb
index 57e9c67e7b6ecdb68711ec57b5e262b9a12b2b99..1fbeea66baff9d2a58abaf6609ac8d33ba29aecf 100644
--- a/BHPD/01-DNN-Regression.ipynb
+++ b/BHPD/01-DNN-Regression.ipynb
@@ -6,7 +6,8 @@
    "source": [
     "<img width=\"800px\" src=\"../fidle/img/00-Fidle-header-01.svg\"></img>\n",
     "\n",
-    "# <!-- TITLE --> Regression with a Dense Network (DNN)\n",
+    "\n",
+    "# <!-- TITLE --> [REG1] - Regression with a Dense Network (DNN)\n",
     "<!-- DESC --> A Simple regression with a Dense Neural Network (DNN) - BHPD dataset\n",
     "<!-- AUTHOR : Jean-Luc Parouty (CNRS/SIMaP) -->\n",
     "\n",
diff --git a/BHPD/02-DNN-Regression-Premium.ipynb b/BHPD/02-DNN-Regression-Premium.ipynb
index 311c5865a2f044d37eed591ecbb3607d7b43693f..350a322bc68135e8dd778e2089d52ff2e38bd9dc 100644
--- a/BHPD/02-DNN-Regression-Premium.ipynb
+++ b/BHPD/02-DNN-Regression-Premium.ipynb
@@ -4,9 +4,9 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "![Fidle](../fidle/img/00-Fidle-header-01.png)\n",
+    "<img width=\"800px\" src=\"../fidle/img/00-Fidle-header-01.svg\"></img>\n",
     "\n",
-    "# <!-- TITLE --> Regression with a Dense Network (DNN) - Advanced code\n",
+    "# <!-- TITLE --> [REG2] - Regression with a Dense Network (DNN) - Advanced code\n",
     "  <!-- DESC -->  More advanced example of DNN network code - BHPD dataset\n",
     "  <!-- AUTHOR : Jean-Luc Parouty (CNRS/SIMaP) -->\n",
     "\n",
diff --git a/GTSRB/01-Preparation-of-data.ipynb b/GTSRB/01-Preparation-of-data.ipynb
index cb51503e17ebbdb414ebcd4da8542e567da6e3f7..95361920ca10e578943beed559b0a765f15ac167 100644
--- a/GTSRB/01-Preparation-of-data.ipynb
+++ b/GTSRB/01-Preparation-of-data.ipynb
@@ -4,9 +4,9 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "![Fidle](../fidle/img/00-Fidle-header-01.png)\n",
+    "<img width=\"800px\" src=\"../fidle/img/00-Fidle-header-01.svg\"></img>\n",
     "\n",
-    "# <!-- TITLE --> CNN with GTSRB dataset - Data analysis and preparation\n",
+    "# <!-- TITLE --> [GTS1] - CNN with GTSRB dataset - Data analysis and preparation\n",
     "<!-- DESC --> Episode 1: Data analysis and creation of a usable dataset\n",
     "<!-- AUTHOR : Jean-Luc Parouty (CNRS/SIMaP) -->\n",
     "\n",
@@ -664,7 +664,7 @@
    "metadata": {},
    "source": [
     "---\n",
-    "![](../fidle/img/00-Fidle-logo-01_s.png)"
+    "<img width=\"80px\" src=\"../fidle/img/00-Fidle-logo-01.svg\"></img>"
    ]
   }
  ],
diff --git a/GTSRB/02-First-convolutions.ipynb b/GTSRB/02-First-convolutions.ipynb
index b8535119983d5b289eda2d0c2c10f359a3c3e5d3..a9119c502deb25011b612fadf398ce8736082aae 100644
--- a/GTSRB/02-First-convolutions.ipynb
+++ b/GTSRB/02-First-convolutions.ipynb
@@ -4,9 +4,9 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "![Fidle](../fidle/img/00-Fidle-header-01.png)\n",
+    "<img width=\"800px\" src=\"../fidle/img/00-Fidle-header-01.svg\"></img>\n",
     "\n",
-    "# <!-- TITLE --> CNN with GTSRB dataset - First convolutions\n",
+    "# <!-- TITLE --> [GTS2] - CNN with GTSRB dataset - First convolutions\n",
     "<!-- DESC --> Episode 2 : First convolutions and first results\n",
     "<!-- AUTHOR : Jean-Luc Parouty (CNRS/SIMaP) -->\n",
     "\n",
@@ -307,7 +307,7 @@
    "metadata": {},
    "source": [
     "---\n",
-    "![](../fidle/img/00-Fidle-logo-01_s.png)"
+    "<img width=\"80px\" src=\"../fidle/img/00-Fidle-logo-01.svg\"></img>"
    ]
   }
  ],
diff --git a/GTSRB/03-Tracking-and-visualizing.ipynb b/GTSRB/03-Tracking-and-visualizing.ipynb
index 5819f76d534a9471a886eca84e46da611532e770..9a464b2166406c8df1c84e8039b0b4b271d9350d 100644
--- a/GTSRB/03-Tracking-and-visualizing.ipynb
+++ b/GTSRB/03-Tracking-and-visualizing.ipynb
@@ -4,9 +4,9 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "![Fidle](../fidle/img/00-Fidle-header-01.png)\n",
+    "<img width=\"800px\" src=\"../fidle/img/00-Fidle-header-01.svg\"></img>\n",
     "\n",
-    "# <!-- TITLE --> CNN with GTSRB dataset - Monitoring \n",
+    "# <!-- TITLE --> [GTS3] - CNN with GTSRB dataset - Monitoring \n",
     "<!-- DESC --> Episode 3: Monitoring and analysing training, managing checkpoints\n",
     "<!-- AUTHOR : Jean-Luc Parouty (CNRS/SIMaP) -->\n",
     "\n",
@@ -463,7 +463,7 @@
    "metadata": {},
    "source": [
     "---\n",
-    "![](../fidle/img/00-Fidle-logo-01_s.png)"
+    "<img width=\"80px\" src=\"../fidle/img/00-Fidle-logo-01.svg\"></img>"
    ]
   }
  ],
diff --git a/README.md b/README.md
index eb66f65cd3779a30012824d7e79b9729b0810e1f..e2364c96ecdfa07c0075fb988a894bc30ad351b5 100644
--- a/README.md
+++ b/README.md
@@ -37,15 +37,15 @@ Useful information is also available in the [wiki](https://gricad-gitlab.univ-gr
 &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Illustration of the problem of complexity with the polynomial regression
 1. [Logistic regression, in pure Tensorflow](LinearReg/04-Logistic-Regression.ipynb)<br>
 &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Logistic Regression with Mini-Batch Gradient Descent using pure TensorFlow. 
-1. [Regression with a Dense Network (DNN)](BHPD/01-DNN-Regression.ipynb)<br>
+1. [[REG1] - Regression with a Dense Network (DNN)](BHPD/01-DNN-Regression.ipynb)<br>
 &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;A Simple regression with a Dense Neural Network (DNN) - BHPD dataset
-1. [Regression with a Dense Network (DNN) - Advanced code](BHPD/02-DNN-Regression-Premium.ipynb)<br>
+1. [[REG2] - Regression with a Dense Network (DNN) - Advanced code](BHPD/02-DNN-Regression-Premium.ipynb)<br>
 &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;More advanced example of DNN network code - BHPD dataset
-1. [CNN with GTSRB dataset - Data analysis and preparation](GTSRB/01-Preparation-of-data.ipynb)<br>
+1. [[GTS1] - CNN with GTSRB dataset - Data analysis and preparation](GTSRB/01-Preparation-of-data.ipynb)<br>
 &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Episode 1: Data analysis and creation of a usable dataset
-1. [CNN with GTSRB dataset - First convolutions](GTSRB/02-First-convolutions.ipynb)<br>
+1. [[GTS2] - CNN with GTSRB dataset - First convolutions](GTSRB/02-First-convolutions.ipynb)<br>
 &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Episode 2 : First convolutions and first results
-1. [CNN with GTSRB dataset - Monitoring ](GTSRB/03-Tracking-and-visualizing.ipynb)<br>
+1. [[GTS3] - CNN with GTSRB dataset - Monitoring ](GTSRB/03-Tracking-and-visualizing.ipynb)<br>
 &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Episode 3: Monitoring and analysing training, managing checkpoints
 1. [CNN with GTSRB dataset - Data augmentation ](GTSRB/04-Data-augmentation.ipynb)<br>
 &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Episode 4: Improving the results with data augmentation
diff --git a/fidle/Charte.ipynb b/fidle/Charte.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..c69dff70c5824f044d8ff664b611df24ad79d65c
--- /dev/null
+++ b/fidle/Charte.ipynb
@@ -0,0 +1,56 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<img width=\"800px\" src=\"../fidle/img/00-Fidle-header-01.svg\"></img>\n",
+    "\n",
+    "# <!-- TITLE --> Titre_du_notebook\n",
+    "<!-- DESC --> Description_du_notebook_et_de_sa_thématique\n",
+    "<!-- AUTHOR : Jean-Luc Parouty (CNRS/SIMaP) -->\n",
+    "\n",
+    "## Objectives :\n",
+    " - Objectif \n",
+    " - Objectif_pédagogique  \n",
+    "\n",
+    "\n",
+    "A_propos_du_dataset\n",
+    "\n",
+    "## What we're going to do :\n",
+    "\n",
+    " - Ceci\n",
+    " - Cela\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "---\n",
+    "<img width=\"80px\" src=\"../fidle/img/00-Fidle-logo-01.svg\"></img>"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}