Tutorial on Using Machine Learning for Activity Recognition Via a Smartphone
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This article provides a tutorial for developing a simple machine learning application in Python. More spe-cifically, the paper considers daily activity recognition using sensors of a smartphone. For development, we used TensorFlow, Skikit learn, NumPy, Pandas, and Matplotlib. The paper explains in detail the main steps of the application development, including data collection and pre-processing, design of the neural network, learning process, and use of a trained model. The overall accuracy of the developed application when recognizing the activity is about 95 %. This paper can be useful for students and specialists who want to start work on machine learning.
1999 ◽
Vol 3
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pp. 427-430
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2020 ◽
Vol 9
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pp. 2011-2017
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Vol 30
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pp. 1093-1099
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2017 ◽
Vol 20
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pp. 1101-1110
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