small cleanup

5uperpalo · Aug 13, 2024 · 48c590f · 48c590f
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diff --git a/README.MD b/README.MD
@@ -1,7 +1,7 @@
 # <img src="docs/sources/assets/images/logo.png" style="height:2em; vertical-align: middle;">
 Customer churn predictor for an assignment below.
 
-Documentation: https://5uperpalo.github.io/ecovadis_assignment/
+Documentation: https://5uperpalo.github.io/churnpred/
 
 ```
 In this assignment you're tasked with developing a machine learning solution for churn prediction to identify which customers are likely to leave a service (column "Exited" in the attached dataset). This assignment is meant to assess

diff --git a/docs/site/cicd.html b/docs/site/cicd.html
@@ -684,7 +684,7 @@
 
 
 <h1 id="cicd">CI/CD<a class="headerlink" href="#cicd" title="Permanent link">&para;</a></h1>
-<p>This section includes some ideas for model developmnet and deployment within Azure services - i.e. EcoVadis cloud services vendor.</p>
+<p>This section includes some ideas for model developmnet and deployment within Azure services.</p>
 <ul>
 <li>MLFlow for experiment tracking and endpoint deployment</li>
 <li><a href="https://mlflow.org/docs/1.25.1/python_api/mlflow.azureml.html">https://mlflow.org/docs/1.25.1/python_api/mlflow.azureml.html</a></li>

diff --git a/docs/site/cicd.md b/docs/site/cicd.md
@@ -1,6 +1,6 @@
 # CI/CD
 
-This section includes some ideas for model developmnet and deployment within Azure services - i.e. EcoVadis cloud services vendor.
+This section includes some ideas for model developmnet and deployment within Azure services.
 
 * MLFlow for experiment tracking and endpoint deployment
   * https://mlflow.org/docs/1.25.1/python_api/mlflow.azureml.html

diff --git a/docs/site/search/search_index.json b/docs/site/search/search_index.json
diff --git a/docs/site/sitemap.xml.gz b/docs/site/sitemap.xml.gz
diff --git a/docs/sources/cicd.md b/docs/sources/cicd.md
@@ -1,6 +1,6 @@
 # CI/CD
 
-This section includes some ideas for model developmnet and deployment within Azure services - i.e. EcoVadis cloud services vendor.
+This section includes some ideas for model developmnet and deployment within Azure services.
 
 * MLFlow for experiment tracking and endpoint deployment
   * https://mlflow.org/docs/1.25.1/python_api/mlflow.azureml.html