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is In Organization
Yes
description
This was my Master's project where i was involved using a dataset from Wireless Sensor Data Mining Lab (WISDM) to build a machine learning model to predict basic human activities using a smartphone accelerometer, Using Tensorflow framework, recurrent neural nets and multiple stacks of Long-short-term memory units(LSTM) for building a deep network. After the model was trained, it was saved and exported to an android application and the predictions were made using the model and the interface to speak out the results using text-to-speech API.
description
The library for web and native user interfaces.
homepage
homepage
https://react.dev
url
https://githubhelp/dscha09/human-activity-recognition-using-recurrent-neural-nets-rnn-lstm-and-tensorflow-on-smartphones
url
https://githubhelp/facebook/react
disk Usage
145845
dis kUsage
564006
stargazer Count
1
stargazer Count
226226
forkCount
0
forkCount
46147
watcher Count
1
watcher Count
226226
created At
2018-05-03
created At
2013-05-25
license Info
license Info
MIT License
issues
0
issues
50
languages
1
languages
12
repository Topics
0
repository Topics
6
owner
dscha09
owner
facebook
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owner Avatar
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other
other

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