.. Copyright 2024 Intel Corporation
..
.. Licensed under the Apache License, Version 2.0 (the "License");
.. you may not use this file except in compliance with the License.
.. You may obtain a copy of the License at
..
..     http://www.apache.org/licenses/LICENSE-2.0
..
.. Unless required by applicable law or agreed to in writing, software
.. distributed under the License is distributed on an "AS IS" BASIS,
.. WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
.. See the License for the specific language governing permissions and
.. limitations under the License.


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|intelex| Tutorials & Case Studies
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Explore the tutorials & case studies to help you to harness the full potential of |intelex|.

Tutorials
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.. grid:: 3

   .. grid-item-card:: Introduction to scikit-learn* Essentials for Machine Learning
      :link: https://www.intel.com/content/www/us/en/developer/videos/introduction-to-scikit-learn-essentials-for-ml.html
      :padding: 1

      An overview of scikit-learn essentials.

   .. grid-item-card:: Advanced scikit-learn* Essentials for Machine Learning
      :link: https://www.intel.com/content/www/us/en/developer/videos/advanced-scikit-learn-essentials-for-ml.html
      :padding: 1

      Special technique to perform scikit-learn computation on Intel GPUs.

   .. grid-item-card:: Develop Efficient AI Solutions with Accelerated Machine Learning
      :link: https://www.intel.com/content/www/us/en/developer/videos/accelerated-machine-learning-for-ai-solutions.html
      :padding: 1

      Techniques for maximizing Intel® Extension for Scikit-learn*.

   .. grid-item-card:: Getting started with classical Machine Learning Frameworks using Google Colaboratory
      :link: https://community.intel.com/t5/Blogs/Tech-Innovation/Artificial-Intelligence-AI/Getting-started-with-classical-Machine-Learning-Frameworks-using/post/1450139
      :padding: 1

      Simple Installation of Intel® Extension for Scikit-learn* on Google Colaboratory.

   .. grid-item-card:: Accelerate Machine Learning Workloads: K-means and GPairs Algorithms
      :link: https://www.intel.com/content/www/us/en/developer/videos/accelerate-ml-workloads-k-means-gpairs-algorithms.html
      :padding: 1

      An introduction to Intel® Extension for Scikit-learn*.

   .. grid-item-card:: Benchmarking Intel® Extension for Scikit-learn*: How Much Faster Is It?
      :link: https://www.intel.com/content/www/us/en/developer/articles/technical/benchmarking-intel-extension-for-scikit-learn.html
      :padding: 1

      Explore and compare the performance of the Intel Extension for Scikit-learn* vs. stock Scikit-learn*.

   .. grid-item-card:: Drive Innovation & Performance into Your scikit-learn* Machine Learning Tasks
      :link: https://www.intel.com/content/www/us/en/developer/videos/drive-innovation-performance-scikit-learn-ml-tasks.html
      :padding: 1

      An overview of scikit-learn essentials.

Case Studies
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.. 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 Intel® 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

      Leveraging Open-Source AI Technologies with Red Hat OpenShift* Data Science and Intel® Architecture.

   .. grid-item-card:: HippoScreen Improves AI Performance by 2.4x with oneAPI Tools
      :link: https://www.intel.com/content/www/us/en/developer/articles/case-study/hipposcreen-boosts-ai-performance-2-4x-with-oneapi.html
      :padding: 1

      The neurotechnology startup used |intelex| to the improve efficiency and build times of deep-learning models used in its Brain Waves AI system.