fix_small_issues

nbs/docs/getting-started/1_introduction.ipynb

@@ -36,7 +36,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "**Get started with our [QuickStart guide](/getting-started-timegpt_quickstart), walk through tutorials on the different capabilities, and learn from real-world use cases in our documentation.**"
+    "**Get started with our [QuickStart guide](/docs/getting-started-timegpt_quickstart), walk through tutorials on the different capabilities, and learn from real-world use cases in our documentation.**"
    ]
   },
   {
@@ -66,7 +66,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "<img src=\"https://github.com/Nixtla/nixtla/blob/main/nbs/img/timegpt-arch.png?raw=true\" alt=\"Figure 1. TimeGPT architecture\">"
+    "<img src=\"https://github.com/Nixtla/nixtla/blob/main/nbs/img/timegpt-arch.png?raw=true\" alt=\"Figure 1. TimeGPT architecture\" />"
    ]
   },
   {

nbs/docs/getting-started/3_setting_up_your_api_key.ipynb

@@ -33,7 +33,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "<img src=\"https://github.com/Nixtla/nixtla/blob/main/nbs/img/api_key_process.png?raw=true\" alt=\"Figure 1. API key set up process\">"
+    "<img src=\"https://github.com/Nixtla/nixtla/blob/main/nbs/img/api_key_process.png?raw=true\" alt=\"Figure 1. API key set up process\" />"
    ]
   },
   {

nbs/docs/getting-started/7_faq.ipynb

@@ -444,7 +444,7 @@
     "\n",
     "In addtion, we are currently developing a self-hosted version of `TimeGPT`, tailored for the unique security requirements of enterprise data. This version is currently in beta. If you are interested in exploring this option, please contact us at [email protected].\n",
     "\n",
-    "</detaila>"
+    "</details>"
    ]
   },
   {
@@ -485,7 +485,7 @@
     "<summary><strong>Error message: Too many requests</strong></summary>\n",
     "\n",
     "``` python\n",
-    "ApiError: status_code: 429, body: {'data': None, 'message': 'Too many requests', 'details': 'You need to add a payment method to continue using the API, do so from https://dashboard.nixtla.io', 'code': 'A21', 'requestID': 'NCJDK7KSJ6', 'support': 'If you have questions or need support, please email [email protected]’}\n",
+    "ApiError: status_code: 429, body: {'data': None, 'message': 'Too many requests', 'details': 'You need to add a payment method to continue using the API, do so from https://dashboard.nixtla.io', 'code': 'A21', 'requestID': 'NCJDK7KSJ6', 'support': 'If you have questions or need support, please email [email protected]'}\n",
     "```\n",
     "\n",
     "**Solution:** This error occurs when you have exhausted your free credits and need to add a payment method to continue using `TimeGPT`. You can add a payment method in the `Billing` section of your [dashboard](https://dashboard.nixtla.io/).\n",

nbs/docs/tutorials/07_loss_function_finetuning.ipynb

@@ -307,7 +307,7 @@
     "\\\n",
     "**Mean absolute error (MAE)**\\\n",
     "\\\n",
-    "<img src=\"https://latex.codecogs.com/svg.image?\\mathrm{MAE}(\\mathbf{y}_{\\tau}, \\mathbf{\\hat{y}}_{\\tau}) = \\frac{1}{H} \\sum^{t+H}_{\\tau=t+1} |y_{\\tau} - \\hat{y}_{\\tau}|\">\n",
+    "<img src=\"https://latex.codecogs.com/svg.image?\\mathrm{MAE}(\\mathbf{y}_{\\tau}, \\mathbf{\\hat{y}}_{\\tau}) = \\frac{1}{H} \\sum^{t+H}_{\\tau=t+1} |y_{\\tau} - \\hat{y}_{\\tau}|\" />\n",
     "\n",
     "- Robust to outliers\n",
     "- Easy to understand\n",
@@ -316,7 +316,7 @@
     "\n",
     "**Mean squared error (MSE)**\\\n",
     "\\\n",
-    "<img src=\"https://latex.codecogs.com/svg.image?\\mathrm{MSE}(\\mathbf{y}_{\\tau}, \\mathbf{\\hat{y}}_{\\tau}) = \\frac{1}{H} \\sum^{t+H}_{\\tau=t+1} (y_{\\tau} - \\hat{y}_{\\tau})^{2}\">\n",
+    "<img src=\"https://latex.codecogs.com/svg.image?\\mathrm{MSE}(\\mathbf{y}_{\\tau}, \\mathbf{\\hat{y}}_{\\tau}) = \\frac{1}{H} \\sum^{t+H}_{\\tau=t+1} (y_{\\tau} - \\hat{y}_{\\tau})^{2}\" />\n",
     "\n",
     "- You want to penalize large errors more than small ones\n",
     "- Sensitive to outliers\n",
@@ -325,14 +325,14 @@
     "\n",
     "**Root mean squared error (RMSE)**\\\n",
     "\\\n",
-    "<img src=\"https://latex.codecogs.com/svg.image?\\mathrm{RMSE}(\\mathbf{y}_{\\tau}, \\mathbf{\\hat{y}}_{\\tau}) = \\sqrt{\\frac{1}{H} \\sum^{t+H}_{\\tau=t+1} (y_{\\tau} - \\hat{y}_{\\tau})^{2}}\">\n",
+    "<img src=\"https://latex.codecogs.com/svg.image?\\mathrm{RMSE}(\\mathbf{y}_{\\tau}, \\mathbf{\\hat{y}}_{\\tau}) = \\sqrt{\\frac{1}{H} \\sum^{t+H}_{\\tau=t+1} (y_{\\tau} - \\hat{y}_{\\tau})^{2}}\" />\n",
     "\n",
     "- Brings the MSE back to original units of data\n",
     "- Penalizes large errors more than small ones\n",
     "\n",
     "**Mean absolute percentage error (MAPE)**\\\n",
     "\\\n",
-    "<img src=\"https://latex.codecogs.com/svg.image?\\mathrm{MAPE}(\\mathbf{y}_{\\tau}, \\mathbf{\\hat{y}}_{\\tau}) = \\frac{1}{H} \\sum^{t+H}_{\\tau=t+1} \\frac{|y_{\\tau}-\\hat{y}_{\\tau}|}{|y_{\\tau}|}\">\n",
+    "<img src=\"https://latex.codecogs.com/svg.image?\\mathrm{MAPE}(\\mathbf{y}_{\\tau}, \\mathbf{\\hat{y}}_{\\tau}) = \\frac{1}{H} \\sum^{t+H}_{\\tau=t+1} \\frac{|y_{\\tau}-\\hat{y}_{\\tau}|}{|y_{\\tau}|}\" />\n",
     "\n",
     "- Easy to understand for non-technical stakeholders\n",
     "- Expressed as a percentage\n",
@@ -341,7 +341,7 @@
     "\n",
     "**Symmmetric mean absolute percentage error (sMAPE)**\\\n",
     "\\\n",
-    "<img src=\"https://latex.codecogs.com/svg.image?\\mathrm{SMAPE}_{2}(\\mathbf{y}_{\\tau}, \\mathbf{\\hat{y}}_{\\tau}) = \\frac{1}{H} \\sum^{t+H}_{\\tau=t+1} \\frac{|y_{\\tau}-\\hat{y}_{\\tau}|}{|y_{\\tau}|+|\\hat{y}_{\\tau}|}\">\n",
+    "<img src=\"https://latex.codecogs.com/svg.image?\\mathrm{SMAPE}_{2}(\\mathbf{y}_{\\tau}, \\mathbf{\\hat{y}}_{\\tau}) = \\frac{1}{H} \\sum^{t+H}_{\\tau=t+1} \\frac{|y_{\\tau}-\\hat{y}_{\\tau}|}{|y_{\\tau}|+|\\hat{y}_{\\tau}|}\" />\n",
     "\n",
     "- Fixes bias of MAPE\n",
     "- Equally senstitive to over and under forecasting\n",

nbs/docs/tutorials/08_cross_validation.ipynb

@@ -180,7 +180,7 @@
    "source": [
     "The `cross_validation` method within the `TimeGPT` class is an advanced functionality crafted to perform systematic validation on time series forecasting models. This method necessitates a dataframe comprising time-ordered data and employs a rolling-window scheme to meticulously evaluate the model's performance across different time periods, thereby ensuring the model's reliability and stability over time. The animation below shows how TimeGPT performs cross-validation.\n",
     "\n",
-    "<img src=\"https://raw.githubusercontent.com/Nixtla/statsforecast/main/nbs/imgs/ChainedWindows.gif\" alt=\"Rolling-window cross-validation\"> \n",
+    "<img src=\"https://raw.githubusercontent.com/Nixtla/statsforecast/main/nbs/imgs/ChainedWindows.gif\" alt=\"Rolling-window cross-validation\" /> \n",
     "\n",
     "Key parameters include `freq`, which denotes the data's frequency and is automatically inferred if not specified. The `id_col`, `time_col`, and `target_col` parameters designate the respective columns for each series' identifier, time step, and target values. The method offers customization through parameters like `n_windows`, indicating the number of separate time windows on which the model is assessed, and `step_size`, determining the gap between these windows. If `step_size` is unspecified, it defaults to the forecast horizon `h`. \n",
     "\n",

nbs/docs/tutorials/13_bounded_forecasts.ipynb

@@ -151,14 +151,27 @@
     "We use the [annual egg prices](https://github.com/robjhyndman/fpp3package/tree/master/data) dataset from [Forecasting, Principles and Practices](https://otexts.com/fpp3/). We expect egg prices to be strictly positive, so we want to bound our forecasts to be positive. "
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "0fa6759e",
+   "metadata": {},
+   "source": [
+    "::: {.callout-note}\n",
+    "You can install `pyreadr` with `pip`:\n",
+    "    \n",
+    "```shell\n",
+    "pip install pyreadr\n",
+    "```\n",
+    ":::"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
    "id": "31b1e602-f8ee-49c4-8819-fcc093d64ab1",
    "metadata": {},
    "outputs": [],
    "source": [
-    "!pip install pyreadr\n",
     "import pyreadr\n",
     "from pathlib import Path\n",
     "\n",

nbs/docs/tutorials/14_hierarchical_forecasting.ipynb

@@ -369,6 +369,20 @@
     "Using the `aggregate` function from `HierarchicalForecast` we can get the full set of time series."
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "86609206",
+   "metadata": {},
+   "source": [
+    "::: {.callout-note}\n",
+    "You can install `hierarchicalforecast` with `pip`:\n",
+    "    \n",
+    "```shell\n",
+    "pip install hierarchicalforecast\n",
+    "```\n",
+    ":::"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,

nbs/docs/use-cases/2_bitcoin_price_prediction.ipynb

@@ -56,7 +56,7 @@
     {
      "data": {
       "text/markdown": [
-       "[![](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/Nixtla/nixtla/blob/main/nbs/docs/use_cases/1_forecasting_web_traffic.ipynb)"
+       "[![](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/Nixtla/nixtla/blob/main/nbs/docs/use-cases/2_bitcoin_price_prediction.ipynb)"
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -68,7 +68,7 @@
    ],
    "source": [
     "#| echo: false\n",
-    "colab_badge('docs/use_cases/2_bitcoin_price_prediction')"
+    "colab_badge('docs/use-cases/2_bitcoin_price_prediction')"
    ]
   },
   {

nbs/mint.json

@@ -20,10 +20,6 @@
     "url": "https://github.com/Nixtla/nixtla"
   },
   "navigation": [
-    {
-      "group": "",
-      "pages": ["index.html"]
-    },
     {
       "group": "Getting Started",
       "pages": [
@@ -46,7 +42,7 @@
             "docs/capabilities/forecast/longhorizon.html",
             "docs/capabilities/forecast/multiple_series.html",
             "docs/capabilities/forecast/finetuning.html",
-            "docs/capabilities/forecast/custom_loss_functions.html",
+            "docs/capabilities/forecast/custom_loss_function.html",
             "docs/capabilities/forecast/cross_validation.html",
             "docs/capabilities/forecast/prediction_intervals.html",
             "docs/capabilities/forecast/irregular_timestamps.html"

nbs/sidebar.yml

@@ -3,7 +3,6 @@ website:
   sidebar:
     collapse-level: 1
     contents:
-      - index.ipynb
       - text: "--"
       - section: "Getting Started"
         contents: docs/getting-started/*