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  • Members: Free
    IEEE Members: $11.00
    Non-members: $15.00
    Pages/Slides: 22
01 Mar 2022

Learning Objectives –
1. to impart basic understanding of machine learning concept to audience .
2. To explain Python programming as a back end tool.
3. To explain applications of machine learning in Smart Microgrids
The session is broadly divided in three parts, as follows-
1. Part I-Review of Grid System, Microgrid, Smart Grid, Smart Microgrid.
2. Part II -Review of Machine Learning Concepts, Python programming and IoT
3. Part III-Applications of Machine Learning Tools in Microgrid – ANN based OR gate, SVM, K means Clustering, Decision tree, Linear Regression, Virtual Meter, Summation meters, Theft detection, Thermography.
Conclusion- The audience would learn about basic fundamentals of machine learning and their applications in Microgrids. They would be able to develop small applications based on this topic.

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