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Rapid developments in hardware, software, and communication technologies have allowed the emergence of Internet-connected sensory devices that provide observation and data measurement from the physical world. Internet-connected devices technology, continues to extend the current Internet by providing connectivity and interaction between the physical and cyber worlds. In addition to increased volume, the IoT generates Big Data characterized by velocity in terms of time and location dependency, with a variety of multiple modalities and varying data quality. This workshop discusses the different machine learning methods that deal with the challenges in IoT data. The potential and challenges of machine learning for IoT
data analytics will also be discussed. This would be a great platform for the interaction of students with reputed scientists and academicians. It also opens up vistas by disseminating the recent research for industrial applications. Further, it paves way for industrialists to innovate modern products which helps in ease of processing and help for the societal development.
Paper Presentation Topics
An Introduction to IoT
An Introduction to Machine Learning and its
Unsupervised Algorithms for IoT Analysis(From
Modeling to visualization)
· KMeans Clustering
· KNN Algorithms
Supervised Algorithms for IoT(From Modeling to Visualization)
· Bayesian Classi
How to reach Sri Ramakrishna Institute of Technology, Coimbatore
BY bus from Gandhipuram
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