diff --git a/README.md b/README.md index 3d8a620..8282161 100644 --- a/README.md +++ b/README.md @@ -11,7 +11,7 @@ IbisML is a library for building scalable ML pipelines using Ibis: - Preprocess your data at scale on any [Ibis](https://ibis-project.org/)-supported backend. -- Compose [`Recipe`](/reference/core.html#ibisml.Recipe)s with other scikit-learn +- Compose [`Recipe`](/reference/core.html#ibis_ml.Recipe)s with other scikit-learn estimators using [`Pipeline`](https://scikit-learn.org/stable/modules/compose.html#pipeline-chaining-estimators)s. - Seamlessly integrate with [scikit-learn](https://scikit-learn.org/stable/), @@ -20,7 +20,7 @@ IbisML is a library for building scalable ML pipelines using Ibis: ```python import ibis -import ibisml as ml +import ibis_ml as ml # A recipe for a feature engineering pipeline that: # - imputes missing values in numeric columns with their mean diff --git a/docs/_quarto.yml b/docs/_quarto.yml index d3332aa..e0b2cff 100644 --- a/docs/_quarto.yml +++ b/docs/_quarto.yml @@ -88,7 +88,7 @@ format: css: styles.css quartodoc: - package: ibisml + package: ibis_ml title: Reference sidebar: reference/_sidebar.yml dynamic: true @@ -98,7 +98,7 @@ quartodoc: signature_name: short sections: - title: Core - package: ibisml + package: ibis_ml contents: - kind: page path: core @@ -136,7 +136,7 @@ quartodoc: - title: Steps desc: Define steps in a recipe - package: ibisml + package: ibis_ml contents: - kind: page path: steps-imputation diff --git a/docs/index.qmd b/docs/index.qmd index d6511ce..6da7806 100644 --- a/docs/index.qmd +++ b/docs/index.qmd @@ -11,7 +11,7 @@ hide-description: true - Preprocess your data at scale on any [Ibis](https://ibis-project.org/)-supported backend. -- Compose [`Recipe`](/reference/core.html#ibisml.Recipe)s with other scikit-learn +- Compose [`Recipe`](/reference/core.html#ibis_ml.Recipe)s with other scikit-learn estimators using [`Pipeline`](https://scikit-learn.org/stable/modules/compose.html#pipeline-chaining-estimators)s. - Seamlessly integrate with [scikit-learn](https://scikit-learn.org/stable/), @@ -23,7 +23,7 @@ hide-description: true ### Install IbisML ```bash -pip install ibisml +pip install ibis-ml ``` ### Create your first recipe @@ -34,7 +34,7 @@ mean of each numeric column and then normalize numeric data to have a standard d of one and a mean of zero. ```{python} -import ibisml as ml +import ibis_ml as ml imputer = ml.ImputeMean(ml.numeric()) scaler = ml.ScaleStandard(ml.numeric()) diff --git a/docs/tutorial/index.ipynb b/docs/tutorial/index.ipynb index be6c9e0..c1a3330 100644 --- a/docs/tutorial/index.ipynb +++ b/docs/tutorial/index.ipynb @@ -532,7 +532,7 @@ "metadata": {}, "outputs": [], "source": [ - "import ibisml as ml\n", + "import ibis_ml as ml\n", "\n", "flights_rec = ml.Recipe(\n", " ml.ExpandDate(\"date\", components=[\"dow\", \"month\"]),\n", @@ -1095,7 +1095,7 @@ " /* fitted */\n", " background-color: var(--sklearn-color-fitted-level-3);\n", "}\n", - "
Pipeline(steps=[('flights_rec', <ibisml.core.Recipe object at 0x149360730>),\n",
+       "
Pipeline(steps=[('flights_rec', <ibis_ml.core.Recipe object at 0x149360730>),\n",
        "                ('mod',\n",
        "                 <class 'skorch.classifier.NeuralNetClassifier'>[initialized](\n",
        "  module_=MyModule(\n",
@@ -1106,7 +1106,7 @@
        "    (output): Linear(in_features=10, out_features=2, bias=True)\n",
        "    (softmax): Softmax(dim=-1)\n",
        "  ),\n",
-       "))])
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