DOC: Fix broken links (#2422)

Author: david-cortes-intel

doc/sources/distributed-mode.rst

@@ -25,7 +25,7 @@ SPMD (multi-GPU distributed mode)
 Several :doc:`GPU-supported algorithms <oneapi-gpu>`
 also provide distributed, multi-GPU computing capabilities via integration with |mpi4py|. The prerequisites
 match those of GPU computing, along with an MPI backend of your choice (`Intel MPI recommended
-<https://www.intel.com/content/www/us/en/developer/tools/oneapi/mpi-library.html#gs.dcan6r>`_, available
+<https://www.intel.com/content/www/us/en/developer/tools/oneapi/mpi-library.html>`_, available
 via ``impi_rt`` python package) and the |mpi4py| python package. If using |sklearnex|
 `installed from sources <https://github.com/uxlfoundation/scikit-learn-intelex/blob/main/INSTALL.md#build-from-sources>`_,
 ensure that the spmd_backend is built.

doc/sources/samples.rst

@@ -20,7 +20,7 @@ Samples
 
 The following samples are also provided as Jupyter notebooks in |sklearnex| repository.
 If you want to run them locally, refer to `these instructions
-<https://github.com/uxlfoundation/scikit-learn-intelex/tree/main/examples/notebooks#snake-intelr-extension-for-scikit-learn-notebooks>`_.
+<https://github.com/uxlfoundation/scikit-learn-intelex/blob/main/examples/notebooks/README.md>`_.
 
 .. rubric:: Classification Tasks
 

doc/sources/tutorials.rst

@@ -71,12 +71,6 @@ Case Studies
 
 .. grid:: 3
 
-   .. grid-item-card:: Greener Machine Learning Computing with Intel® AI Acceleration
-      :link: https://www.intel.com/content/www/us/en/developer/articles/case-study/greener-machine-learning-with-intel-ai.html
-      :padding: 1
-
-      Lowering the Environmental Impact of AI Workloads by 7x using Extension for Scikit-learn*.
-
    .. grid-item-card:: Supply Chain Optimization at Enterprise Scale
       :link: https://www.intel.com/content/www/us/en/developer/articles/technical/supply-chain-optimization-at-enterprise-scale.html
       :padding: 1