Predictive Maintenance: Unsupervised and Supervised Machine Learning

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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.

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Thank you very much guys for this amazing work. I have got MATLAB installed on my machine and there are many examples but couldn’t find this one. Would be highly appreciated if you could share the script with us. Thanks

kammelna
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Great Video. However, I would love to know how you got the TTF classes.

ubongikafia
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At time 23:59 principal component analysis graph is shown. Could someone tell me what the number of the PC means? Is it the parameter? Which means how the number 1, 2, ... are assigned automatically?

srinivasalagesan
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2:10 how to make this real-time prediction app?do you have any tutorials?

devisnugroho
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Are the principal components here representing the sensor data or PCA does not have any physical meaning?

srinivasalagesan
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Can we have the dataset to experiment on it please?

samikzr
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Can anyone share the dataset for this project?

satyajithalder
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Can you please share where could i find this dataset?

rushabhparikh
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Nice, sir can I use this method for 50kw Hydraulic transmission power unit. I need to know RUL of our system

naeemfaiz
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may i get the data used in this tutorial

TheShubham
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what machine learning or deep learning algorithms are most relevant in predictive maintenance, like for mechanical machinery? I want to focus on them.
thank you in advance.

naviddavanikabir