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I am doing a project on mobile sensor Data ,I haven't used neural networks before on this type of data The data is 20750 subsamples extracted from the 1945 collected samples provided in a single .csv file. Each of them contains 3 seconds of non-overlapping data of the corresponding activity. Arrangement of information: Col. 1–300, 301–600, 601–900 ➞ Accelerometer X, Y, Z axes readings Col. 901–1200, 1201–1500, 1501–1800 ➞ Gyro X, Y, Z axes readings Col. 1801 ➞ Class ID (0 to 17, in the order mentioned above) Col. 1802 ➞ length of each channel data in the subsample Col. 1803 ➞ serial no. of the subsample

Is it possible to use LSTM here , as the data sequence is in single row rather sequence of rows . If not , which neural network can we use

Edited : Image included 1800 columns data from 2 sensors

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  • $\begingroup$ Can you please post an exemplar table of the data structure? $\endgroup$
    – hH1sG0n3
    Nov 19 at 13:20

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