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Sign Language Recognition using scikit-learn* (sklearn): Developer Spotlight

Ramya_Ravi
Employee
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American Sign Language (ASL) is a primary and natural language that serves as the prime sign language of Deaf communities. ASL is communicated by movements of the hands and face. Sign Language Recognition technology is a computational process that involves recognizing actions from sign languages. This is an important problem to find a solution, in the digital world to bridge the communication gap that is faced by deaf people communities.

Vatika Agrawal in her blog proposed a solution to Sign Language Recognition using Hand landmark model (using MediaPipe), Random Forest Classifier and Intel® Extension for Scikit-learn*.

The blog explains the various steps involved in the project:

  1. Installation of required libraries.
  2. Data Preprocessing
  3. Model Training
  4. Model Testing

Read and learn more about the project at Sign Language Recognition using MediaPipe and Random Forest— Intel oneAPI Optimized Scikit-Learn Library.

Learn more about Intel Extension for Scikit-learn!!!

Intel Extension for Scikit-learn: This Intel Extension seamlessly speeds up your scikit-learn applications for Intel® architectures across single and multi-node configurations. Also, this extension package dynamically patches scikit-learn estimators while improving performance for your machine learning algorithms. By using Scikit-learn with this extension, the performance for training and inference can be improved up to 100x with the equivalent mathematical accuracy.

Download Intel Extension for Scikit-learn as part of the Intel® AI Analytics Toolkit (AI Kit).

What’s Next?

We encourage you to learn more about and incorporate Intel’s other AI/ML Framework optimizations and end-to-end portfolio of tools into your AI workflow. Also, visit AI & ML page covering Intel’s AI software development resources for preparing, building, deploying, and scaling your AI solutions.

For more details about the new 4th Gen Intel® Xeon® Scalable processors, visit Intel's AI Solution Platform portal where you can learn how Intel is empowering developers to run end-to-end AI pipelines on these powerful CPUs.

About the Author:

Vatika Agrawal is currently pursuing her bachelor’s in computer science at Sikkim Manipal Institute of Technology in Sikkim, India. Her major interests are artificial intelligence and machine learning.

 

About the Author
Product Marketing Engineer bringing cutting edge AI/ML solutions and tools from Intel to developers.