87 adjust example folder filenames

examples/MEXICO_retrain_predict_example.ipynb → examples/retrain_predict_example.ipynb

@@ -1,10 +1,11 @@
 {
  "cells": [
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Exemplo de uso para treinar o modelo\n",
+    "# Usage example to train the model\n",
     "\n",
     "Welcome to the Hygia Boilerplate! This resource is designed to help data scientists understand and utilize the full capabilities of the Hygia library. The Hygia library provides a comprehensive suite of tools for pre-processing, feature engineering, model training, and prediction. By using this boilerplate, you will gain a deeper understanding of how to effectively use the library to perform various tasks in the data science pipeline.\n",
     "\n",
@@ -24,6 +25,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -56,6 +58,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -79,6 +82,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -117,6 +121,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -259,6 +264,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -354,6 +360,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -386,6 +393,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -425,6 +433,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -461,6 +470,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [

examples/MEXICO_retrain_sets copy.ipynb → examples/retrain_sets copy.ipynb

@@ -1,10 +1,11 @@
 {
  "cells": [
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Exemplo de uso para treinar o modelo\n",
+    "# Usage example to train the model\n",
     "\n",
     "Welcome to the Hygia Boilerplate! This resource is designed to help data scientists understand and utilize the full capabilities of the Hygia library. The Hygia library provides a comprehensive suite of tools for pre-processing, feature engineering, model training, and prediction. By using this boilerplate, you will gain a deeper understanding of how to effectively use the library to perform various tasks in the data science pipeline.\n",
     "\n",
@@ -77,6 +78,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -115,6 +117,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -138,6 +141,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -176,6 +180,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -266,6 +271,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -363,6 +369,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -395,6 +402,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -434,6 +442,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -470,6 +479,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [

examples/MEXICO_retrain_sets.ipynb → examples/retrain_sets.ipynb

@@ -1,10 +1,11 @@
 {
  "cells": [
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Exemplo de uso para treinar o modelo\n",
+    "# Usage example to train the model\n",
     "\n",
     "Welcome to the Hygia Boilerplate! This resource is designed to help data scientists understand and utilize the full capabilities of the Hygia library. The Hygia library provides a comprehensive suite of tools for pre-processing, feature engineering, model training, and prediction. By using this boilerplate, you will gain a deeper understanding of how to effectively use the library to perform various tasks in the data science pipeline.\n",
     "\n",
@@ -84,6 +85,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -122,6 +124,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -145,6 +148,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -183,6 +187,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -249,6 +254,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -346,6 +352,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -378,6 +385,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -417,6 +425,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -453,6 +462,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [

examples/yaml_example.ipynb

@@ -1,6 +1,7 @@
 {
  "cells": [
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -39,7 +40,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.16"
+   "version": "3.10.11"
   },
   "vscode": {
    "interpreter": {