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Human Activity Recognition Using Recurrent Neural Nets Rnn Lstm And Tensorflow On Smartphones ⭐ 46

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

Repugnant Pickle ⭐ 19

Low effort scraping Python's pickle format in Rust. It is to complete pickle parsing as BeautifulSoup was to complete HTML parsing.

Heart Disease Diagonstician web app

Youtube Clickbait Detector ⭐ 6

Automatically detect clickbait Youtube videos from their metadata with a 96% F1 score.

Cyber Bullying Detection Application (CBDA)

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