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.. * 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
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.. *     http://www.apache.org/licenses/LICENSE-2.0
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.. * distributed under the License is distributed on an "AS IS" BASIS,
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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.