California unemployment rate prediction using RNN.
Team Members:
Pritham Sriram Govindaraj
Suraj Vasista Bettadapura Krishna
Sai Harshith Karuneegar Ramesh
Maahi Patel
Explaining The Problem:
Given the California Unemployment data set between 1976 and 2021, we are designing a model to predict the unemployment rate for the latest decade.
Out of the given data, we have extracted the columns that provide us the highest value to perform the prediction.
The final columns are: Month Year Area Total Labor Force Employment Unemployment Area Type
Since, our aim is to predict the unemployment rate, that becomes our label. Label: unemployment rate
Our data set initially consisted of 191127 rows and after preprocessing, we are now with a dataset of 173432 rows. We will be performing the prediction using this dataset.
For detaled information of project refer to the Group 21 - Fifer.docs
For video demonstration refer: https://drive.google.com/file/d/1GVMxKhyI88T4vbHq_VEovSIf3xu_iDf4/view?usp=sharing
License: MIT License
Copyright (c) 2022 SURAJ VASHISTA B K
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