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Deep Learning RNN simulation with temporal data

In this simulation employing an example RNN (Recurrent neural network) dataset describing the evolution of the employment status of 25 000 employees, year after year: each sequence corresponds to 10 consecutive years, where each year describes a job situation, comprising 3 components (see the jupyter notebook file for details).

If you run this simulation in eg. VS code, make sure to have all the latest pandas, numpy, seaborn, matplotlib, tensorflow and keras dependencies installed, as well jupyter notebook extensions fully setup to smoothly execute the simulation.

The simulation is highly guided step-by-step to explain what happens for each code block. If you are running into any issues, please contact me directly.

To start, download all files from the repo open the jupyter notebook and execute cell by cell to run the simulation. Have fun learning!

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Deep learning RNN model utilizing temporal data

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