diff --git a/examples/getting_started/1-Introduction.ipynb b/examples/getting_started/1-Introduction.ipynb
index 15d67c8294..7f3d2f7435 100644
--- a/examples/getting_started/1-Introduction.ipynb
+++ b/examples/getting_started/1-Introduction.ipynb
@@ -14,7 +14,7 @@
     "\n",
     "## Why HoloViews?\n",
     "\n",
-    "HoloViews is an [open-source](https://github.com/ioam/holoviews/) Python 2 and 3 library for data analysis and visualization. Python already has excellent tools like numpy, pandas, and xarray for data processing, and bokeh and matplotlib for plotting, so why yet another library?\n",
+    "HoloViews is an [open-source](https://github.com/holoviz/holoviews) Python 2 and 3 library for data analysis and visualization. Python already has excellent tools like numpy, pandas, and xarray for data processing, and bokeh and matplotlib for plotting, so why yet another library?\n",
     "\n",
     "**HoloViews helps you understand your data better, by letting you work seamlessly with both the data *and* its graphical representation.**\n",
     "\n",
@@ -47,7 +47,7 @@
    "source": [
     "This is the standard way to make the numpy and pandas libraries available in the namespace. We recommend always importing HoloViews as ``hv`` and if you haven't already installed HoloViews, check out the install instructions on our [homepage.](http://holoviews.org)\n",
     "\n",
-    "Note that after importing HoloViews as ``hv`` we run ``hv.extension('bokeh')`` to load the bokeh plotting extension, allowing us to generate visualizations with [Bokeh](http://bokeh.pydata.org/). In the next section we will see how you can use other plotting libraries such as [matplotlib](http://matplotlib.org) and even how you can mix and match between them.\n",
+    "Note that after importing HoloViews as ``hv`` we run ``hv.extension('bokeh')`` to load the bokeh plotting extension, allowing us to generate visualizations with [Bokeh](https://bokeh.org). In the next section we will see how you can use other plotting libraries such as [matplotlib](http://matplotlib.org) and even how you can mix and match between them.\n",
     "\n",
     "Now let's load our subway data using pandas:"
    ]
@@ -401,8 +401,8 @@
     "\n",
     "The next getting-started section shows how to do [Customization](2-Customization.ipynb) of the visual appearance of your data, allowing you to highlight the most important features and change the look and feel. Other related topics for deeper study:\n",
     " \n",
-    "* The above plots did not require any special geographic-data support, but when working with larger areas of the Earth's surface (for which curvature becomes significant) or when overlaying data with geographic features, the separate [GeoViews](http://geo.holoviews.org) library provides convenient geo-specific extensions to HoloViews.\n",
-    "* The taxi array data was derived from a very large tabular dataset and rasterized using [datashader](http://github.com/bokeh/datashader), an optional add-on to HoloViews and Bokeh that makes it feasible to work with very large datasets in a web browser."
+    "* The above plots did not require any special geographic-data support, but when working with larger areas of the Earth's surface (for which curvature becomes significant) or when overlaying data with geographic features, the separate [GeoViews](https://geoviews.org) library provides convenient geo-specific extensions to HoloViews.\n",
+    "* The taxi array data was derived from a very large tabular dataset and rasterized using [datashader](https://datashader.org), an optional add-on to HoloViews and Bokeh that makes it feasible to work with very large datasets in a web browser."
    ]
   }
  ],