Tutorial on Using Machine Learning for Activity Recognition Via a Smartphone

Abstract

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.