Predictive Maintenance: Unsupervised and Supervised Machine Learning

Use machine learning techniques such as clustering and classification in MATLAB® to estimate the remaining useful life of equipment. Using data from a real-world example, we will explore importing, pre-processing, and labeling data, as well as selecting features, and training and comparing multiple machine learning models. We will show how MATLAB is used to build prognostics algorithms and take them into production, enabling companies to improve the reliability of their equipment and build new predictive maintenance services. Introduction to Predictive Maintenance with MATLAB: https://bit.ly/2KYOQux Free Predictive Maintenance Toolbox Trial: https://bit.ly/2XphefZ -------------------------------------------------------------------------------------------------------- Get a free product Trial: https://goo.gl/ZHFb5u Learn more about MATLAB: https://goo.gl/8QV7ZZ Learn more about Simulink: https://goo.gl/nqnbLe See What's new in MATLAB and Simulink: https://goo.gl/pgGtod © 2019 The MathWorks, Inc. MATLAB and Simulink are registered trademarks of The MathWorks, Inc. See www.mathworks.com/trademarks for a list of additional trademarks. Other product or brand names may be trademarks or registered trademarks of their respective holders.