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MathWorks Is a Leader in the 2021 Gartner Magic Quadrant for Data Science and Machine Learning Platforms

This is a guest post from Laura Martinez Molera, MathWorks Marketing lead for Machine Learning and Data Science.

We’re thrilled to be recognized by Gartner as a “Leader” for the second year in a row, with the furthest placement for “completeness of vision” of all the Leaders in the Magic Quadrant.

I wanted to share this news and talk about how MathWorks thinks differently about AI.

AI continues to be a strategic priority for many of our customers in asset-centric organizations focusing on engineering and science, financial services, systems development, and operations. We are helping our customers use MATLAB to incorporate deep learning and machine learning in their designs, systems, and operations for applications such as predictive maintenance, automated driving, robotics and autonomous system, and digital twins.

Gartner Magic Quadrant for Data Science and Machine Learning Platforms, Peter Krensky, Carlie Idoine, Erick Brethenoux, Pieter den Hamer, Farhan Choudhary, Afraz Jaffri, Shubhangi Vashisth,1st March 2021.

We believe our recognition as a Leader in the 2021 Gartner Magic Quadrant for Data Science and Machine Learning Platforms demonstrates our ability to help organizations:

  • Equip teams with limited AI or data science skills as well as those with advanced skills to apply AI successfully.
  • Leverage robust composite AI capabilities for developing, integrating, and deploying ensembles of AI techniques including deep learning, machine learning, and reinforcement learning within a single solution.
  • Deploy AI models on embedded devices, edge capabilities, enterprise systems, and the cloud.
  • Use modeling and simulation to tackle integration challenges and reduce risk.

We continue to invest in creating tools and solutions to make AI easy for engineers and scientists in three ways:

  1. Visualization and explainability methods to ensure confidence the AI models accurately represent system behavior.
  2. Deploy deep learning and machine learning models directly as Simulink blocks for use in system simulation, verification, and embedded system development.
  3. Training resources to help engineers and scientists not formally trained in deep learning and machine learning to feel empowered with Coursera courses and more resources.

There’s much more to come this 2021 as we continue to release new features in our products, focused on making MATLAB an easy and productive enterprise engineering platform for AI.

To learn more, check out the new 2021 trends for AI here and the following pages.

 

Artificial Intelligence

Deep Learning

Machine Learning

Have a question for Laura about Gartner? Leave a comment below!

Disclaimers: This graphic was published by Gartner, Inc. as part of a larger research document and should be evaluated in the context of the entire document. The Gartner document is available upon request from MathWorks.

Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner research organization and should not be construed as statements of fact. Gartner disclaims all warranties, express or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.

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