[DOCS] New structure (#323)

Nixtla · Apr 30, 2024 · 4bad565 · 4bad565
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diff --git a/action_files/readme_com/create_readme_docs.sh b/action_files/readme_com/create_readme_docs.sh
@@ -1,7 +1,7 @@
 #!/bin/bash
 
 BASE_DIR="nbs/docs/"
-SUB_DIRS=("getting-started" "tutorials" "how-to-guides" "misc")
+SUB_DIRS=("1_getting_started" "2_capabilities" "2_capabilities/anomaly_detection" "2_capabilities/forecast" "3_deployment" "4_tutorials" "5_use_cases" "7_other_resources")
 
 counter=0
 for sub_dir in "${SUB_DIRS[@]}"; do

diff --git a/nbs/docs/misc/0_faqs.ipynb → nbs/docs/1_getting_started/faqs.ipynb b/nbs/docs/misc/0_faqs.ipynb → nbs/docs/1_getting_started/faqs.ipynb
diff --git a/...ing-started/1_getting_started_short.ipynb → nbs/docs/1_getting_started/quickstart.ipynb b/...ing-started/1_getting_started_short.ipynb → nbs/docs/1_getting_started/quickstart.ipynb
@@ -45,7 +45,7 @@
    ],
    "source": [
     "#| echo: false\n",
-    "colab_badge('docs/getting-started/1_getting_started_short')"
+    "colab_badge('docs/1_getting_started/quickstart')"
    ]
   },
   {

diff --git a/...ting_up_your_authentication_api_key.ipynb → ...ing_started/setting_up_your_api_key.ipynb b/...ting_up_your_authentication_api_key.ipynb → ...ing_started/setting_up_your_api_key.ipynb
@@ -11,7 +11,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Do you give everyone the keys to your house? Likely not. An **API key** is like a key to a house, and should be kept private. It is a unique string of characters that serves as a key to authenticate your requests to `TimeGTP`. This tutorial will explain how to set up your API key when using the Nixtla SDK. \n",
+    "Do you give everyone the keys to your house? Likely not. An **API key** is like a key to a house, and should be kept private. It is a unique string of characters that serves as a key to authenticate your requests to `TimeGPT`. This tutorial will explain how to set up your API key when using the Nixtla SDK. \n",
     "\n",
     "Upon [registration](https://dashboard.nixtla.io/), you will receive an email asking you to confirm your signup. After confirming, you will receive access to your dashboard. There, under `API Keys`, you will find your API key.\n",
     "\n",
@@ -22,7 +22,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "<img src=\"../../assets/2_api_key_process.png?\" alt=\"Figure 1. API key set up process\" width=\"600\"/>"
+    "<img src=\"../../img/api_key_process.png?\" alt=\"Figure 1. API key set up process\" width=\"600\"/>"
    ]
   },
   {
@@ -97,6 +97,7 @@
     "\n",
     "#### Windows\n",
     "For Windows users, open a Powershell window and use the `Set` command to set `NIXTLA_API_KEY`. \n",
+    "\n",
     "``` powershell\n",
     "Set NIXTLA_API_KEY=your_api_key\n",
     "```"

diff --git a/nbs/docs/tutorials/0_anomaly_detection.ipynb → ...lities/anomaly_detection/quickstart.ipynb b/nbs/docs/tutorials/0_anomaly_detection.ipynb → ...lities/anomaly_detection/quickstart.ipynb
@@ -56,7 +56,7 @@
    ],
    "source": [
     "#| echo: false\n",
-    "colab_badge('docs/tutorials/0_anomaly_detection')"
+    "colab_badge('docs/2_capabilities/anomaly_detection/quickstart')"
    ]
   },
   {

diff --git a/nbs/docs/2_capabilities/forecast/quickstart.ipynb b/nbs/docs/2_capabilities/forecast/quickstart.ipynb
diff --git a/nbs/docs/2_capabilities/overview.ipynb b/nbs/docs/2_capabilities/overview.ipynb
@@ -0,0 +1,34 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "6de758ee-a0d2-4b3f-acff-eed419dd17c5",
+   "metadata": {},
+   "source": [
+    "# Capabilities"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5d267032-535b-4b7b-b7d3-d2db8f673af6",
+   "metadata": {},
+   "source": [
+    "TimeGPT can primarily help you solve two tasks:\n",
+    "\n",
+    "1) Forecasting\n",
+    "2) Anomaly detection\n",
+    "\n",
+    "Click on the content on the left to discover the capabilities TimeGPT offers for each of these tasks."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "python3",
+   "language": "python",
+   "name": "python3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/nbs/docs/getting-started/3_azure_ai.ipynb → nbs/docs/3_deployment/azure_ai.ipynb b/nbs/docs/getting-started/3_azure_ai.ipynb → nbs/docs/3_deployment/azure_ai.ipynb
diff --git a/...docs/tutorials/14_bounded_forecasts.ipynb → nbs/docs/4_tutorials/bounded_forecasts.ipynb b/...docs/tutorials/14_bounded_forecasts.ipynb → nbs/docs/4_tutorials/bounded_forecasts.ipynb
@@ -59,7 +59,7 @@
    ],
    "source": [
     "#| echo: false\n",
-    "colab_badge('docs/tutorials/14_bounded_forecasts')"
+    "colab_badge('docs/4_tutorials/bounded_forecasts')"
    ]
   },
   {

diff --git a/.../tutorials/13_categorical_variables.ipynb → ...s/4_tutorials/categorical_variables.ipynb b/.../tutorials/13_categorical_variables.ipynb → ...s/4_tutorials/categorical_variables.ipynb
@@ -13,13 +13,11 @@
    "id": "a81fc39a-c6a0-485d-a3f3-c3a6298928a6",
    "metadata": {},
    "source": [
-    "Categorical variables are external factors that can influence a forecast. These variables take on one of a limited, fixed number of possible values, and induce a grouping of your observations.[^1]\n",
-    "\n",
-    "For example, if you're forecasting daily product demand for a retailer, you could benefit from an event variable that may tell you what kind of event takes place on a given day, for example 'None', 'Sporting', or 'Cultural'.\n",
-    "\n",
-    "To incorporate categorical variables in TimeGPT, you'll need to pair each point in your time series data with the corresponding external data.\n",
-    "\n",
-    "[^1]: https://en.wikipedia.org/wiki/Categorical_variable"
+    "Categorical variables are external factors that can influence a forecast. These variables take on one of a limited, fixed number of possible values, and induce a grouping of your observations.\\\n",
+    "\\\n",
+    "For example, if you're forecasting daily product demand for a retailer, you could benefit from an event variable that may tell you what kind of event takes place on a given day, for example 'None', 'Sporting', or 'Cultural'.\\\n",
+    "\\\n",
+    "To incorporate categorical variables in TimeGPT, you'll need to pair each point in your time series data with the corresponding external data."
    ]
   },
   {
@@ -63,7 +61,7 @@
    ],
    "source": [
     "#| echo: false\n",
-    "colab_badge('docs/tutorials/13_categorical_variables')"
+    "colab_badge('docs/4_tutorials/categorical_variables')"
    ]
   },
   {
@@ -150,11 +148,12 @@
    "id": "bc2bb3db-00e6-44e6-8dc3-a2e0eba7e295",
    "metadata": {},
    "source": [
-    "Let's see an example on predicting sales of products of the [M5 dataset](https://nixtlaverse.nixtla.io/datasetsforecast/m5.html). The M5 dataset contains daily product demand (sales) for 10 retail stores in the US. \n",
-    "\n",
+    "Let's see an example on predicting sales of products of the [M5 dataset](https://nixtlaverse.nixtla.io/datasetsforecast/m5.html). The M5 dataset contains daily product demand (sales) for 10 retail stores in the US.\\\n",
+    "\\\n",
     "First, we load the data using `datasetsforecast`. This returns:\n",
-    "- `Y_df`, containing the sales (`y` column), for each unique product (`unique_id` column) at every timestamp (`ds` column). \n",
-    "- `X_df`, containing additional relevant information for each unique product (`unique_id` column) at every timestamp (`ds` column). "
+    "\n",
+    "* `Y_df`, containing the sales (`y` column), for each unique product (`unique_id` column) at every timestamp (`ds` column). \n",
+    "* `X_df`, containing additional relevant information for each unique product (`unique_id` column) at every timestamp (`ds` column). "
    ]
   },
   {

diff --git a/.../how-to-guides/0_computing_at_scale.ipynb → ...docs/4_tutorials/computing_at_scale.ipynb b/.../how-to-guides/0_computing_at_scale.ipynb → ...docs/4_tutorials/computing_at_scale.ipynb
diff --git a/...computing_at_scale_dask_distributed.ipynb → ...computing_at_scale_dask_distributed.ipynb b/...computing_at_scale_dask_distributed.ipynb → ...computing_at_scale_dask_distributed.ipynb
@@ -52,7 +52,7 @@
    ],
    "source": [
     "#| echo: false\n",
-    "colab_badge('docs/how-to-guides/1_computing_at_scale_with_dask_distributed')"
+    "colab_badge('docs/4_tutorials/computing_at_scale_with_dask_distributed')"
    ]
   },
   {

diff --git a/..._computing_at_scale_ray_distributed.ipynb → .../computing_at_scale_ray_distributed.ipynb b/..._computing_at_scale_ray_distributed.ipynb → .../computing_at_scale_ray_distributed.ipynb
@@ -53,7 +53,7 @@
    ],
    "source": [
     "#| echo: false\n",
-    "colab_badge('docs/how-to-guides/1_computing_at_scale_with_ray_distributed')"
+    "colab_badge('docs/4_tutorials/computing_at_scale_with_ray_distributed')"
    ]
   },
   {

diff --git a/...omputing_at_scale_spark_distributed.ipynb → ...omputing_at_scale_spark_distributed.ipynb b/...omputing_at_scale_spark_distributed.ipynb → ...omputing_at_scale_spark_distributed.ipynb
@@ -53,7 +53,7 @@
    ],
    "source": [
     "#| echo: false\n",
-    "colab_badge('docs/how-to-guides/1_computing_at_scale_with_spark_distributed')"
+    "colab_badge('docs/4_tutorials/computing_at_scale_with_spark_distributed')"
    ]
   },
   {

diff --git a/nbs/docs/tutorials/9_cross_validation.ipynb → nbs/docs/4_tutorials/cross_validation.ipynb b/nbs/docs/tutorials/9_cross_validation.ipynb → nbs/docs/4_tutorials/cross_validation.ipynb
@@ -37,7 +37,7 @@
    "outputs": [],
    "source": [
     "#| echo: false\n",
-    "colab_badge('docs/tutorials/9_cross_validation')"
+    "colab_badge('docs/4_tutorials/cross_validation')"
    ]
   },
   {

diff --git a/...ocs/tutorials/1_exogenous_variables.ipynb → ...ocs/4_tutorials/exogenous_variables.ipynb b/...ocs/tutorials/1_exogenous_variables.ipynb → ...ocs/4_tutorials/exogenous_variables.ipynb
@@ -61,7 +61,7 @@
    ],
    "source": [
     "#| echo: false\n",
-    "colab_badge('docs/tutorials/1_exogenous_variables')"
+    "colab_badge('docs/4_tutorials/exogenous_variables')"
    ]
   },
   {

diff --git a/nbs/docs/tutorials/5_finetuning.ipynb → nbs/docs/4_tutorials/finetuning.ipynb b/nbs/docs/tutorials/5_finetuning.ipynb → nbs/docs/4_tutorials/finetuning.ipynb
@@ -59,7 +59,7 @@
    ],
    "source": [
     "#| echo: false\n",
-    "colab_badge('docs/tutorials/5_finetuning')"
+    "colab_badge('docs/4_tutorials/finetuning')"
    ]
   },
   {

diff --git a/...torials/15_hierarchical_forecasting.ipynb → ..._tutorials/hierarchical_forecasting.ipynb b/...torials/15_hierarchical_forecasting.ipynb → ..._tutorials/hierarchical_forecasting.ipynb
@@ -59,7 +59,7 @@
    ],
    "source": [
     "#| echo: false\n",
-    "colab_badge('docs/tutorials/15_hierarchical_forecasting')"
+    "colab_badge('docs/4_tutorials/hierarchical_forecasting')"
    ]
   },
   {
@@ -156,8 +156,8 @@
    "id": "81f2b918",
    "metadata": {},
    "source": [
-    "<img src=\"../../assets/australia_tourism.png?\" alt=\"Figure 1. Overview of Australia\" width=\"700\"/>\n",
-    "<img src=\"../../assets/australia_hierarchy.png?\" alt=\"Figure 2. Overview of hierarchy of Australia\" width=\"700\"/>"
+    "<img src=\"../../img/australia_tourism.png?\" alt=\"Figure 1. Overview of Australia\" width=\"700\"/>\n",
+    "<img src=\"../../img/australia_hierarchy.png?\" alt=\"Figure 2. Overview of hierarchy of Australia\" width=\"700\"/>"
    ]
   },
   {
@@ -178,7 +178,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "C:\\Users\\ospra\\AppData\\Local\\Temp\\ipykernel_3276\\3753786659.py:6: UserWarning: Could not infer format, so each element will be parsed individually, falling back to `dateutil`. To ensure parsing is consistent and as-expected, please specify a format.\n",
+      "C:\\Users\\ospra\\AppData\\Local\\Temp\\ipykernel_28980\\3753786659.py:6: UserWarning: Could not infer format, so each element will be parsed individually, falling back to `dateutil`. To ensure parsing is consistent and as-expected, please specify a format.\n",
       "  Y_df['ds'] = pd.to_datetime(Y_df['ds'])\n"
      ]
     },

diff --git a/...ocs/tutorials/7_historical_forecast.ipynb → ...ocs/4_tutorials/historical_forecast.ipynb b/...ocs/tutorials/7_historical_forecast.ipynb → ...ocs/4_tutorials/historical_forecast.ipynb
@@ -48,7 +48,7 @@
    ],
    "source": [
     "#| echo: false\n",
-    "colab_badge('docs/tutorials/7_historical_forecast')"
+    "colab_badge('docs/4_tutorials/historical_forecast')"
    ]
   },
   {

diff --git a/nbs/docs/tutorials/2_holidays.ipynb → nbs/docs/4_tutorials/holidays.ipynb b/nbs/docs/tutorials/2_holidays.ipynb → nbs/docs/4_tutorials/holidays.ipynb
@@ -59,7 +59,7 @@
    ],
    "source": [
     "#| echo: false\n",
-    "colab_badge('docs/tutorials/2_holidays')"
+    "colab_badge('docs/4_tutorials/holidays')"
    ]
   },
   {

diff --git a/...cs/tutorials/8_irregular_timestamps.ipynb → ...cs/4_tutorials/irregular_timestamps.ipynb b/...cs/tutorials/8_irregular_timestamps.ipynb → ...cs/4_tutorials/irregular_timestamps.ipynb
@@ -44,7 +44,7 @@
    ],
    "source": [
     "#| echo: false\n",
-    "colab_badge('docs/tutorials/8_irregular_timestamps')"
+    "colab_badge('docs/4_tutorials/irregular_timestamps')"
    ]
   },
   {

diff --git a/nbs/docs/tutorials/12_longhorizon.ipynb → nbs/docs/4_tutorials/longhorizon.ipynb b/nbs/docs/tutorials/12_longhorizon.ipynb → nbs/docs/4_tutorials/longhorizon.ipynb
@@ -50,7 +50,7 @@
    ],
    "source": [
     "#| echo: false\n",
-    "colab_badge('docs/tutorials/12_longhorizon')"
+    "colab_badge('docs/4_tutorials/longhorizon')"
    ]
   },
   {