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Machine Learning
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Expected Credit Loss Model (ECLM) for Agriculture Sector of Pakistan
Expected Credit Loss Model (ECLM) Demonstration through TensorFlow
KSE-100 Index Estimate through Machine Learning
Economy
Estimating GDP Growth of Pakistan through Machine Learning
Population Estimate through Machine Learning
Okun's law suggests that when there is one percent change in unemployment, there is two percent opposit change in GDP.
In other words, it says that GDP and Unemployment have revese correlation and one one increases, the other decreases.
To test the Okun's law, lets use the actual GDP (per capita) and Unemployment data of Pakistan.
As suggested by the Okun's law, our data also shows the same trend.
Year
GDP
Unemployment
1991
410.47402
5.80000
1992
427.57276
5.19999
1993
440.92932
4.30000
1994
433.28858
4.30000
1995
493.66150
5.00000
1996
502.78670
5.40000
1997
483.65293
5.80000
1998
470.24892
5.69999
1999
465.07576
5.90000
2000
533.86241
7.19999
2001
510.65681
7.80000
2002
499.86000
7.80000
2003
563.59434
8.30000
2004
649.80482
7.40000
2005
711.46994
7.69999
2006
873.77027
6.09999
2007
950.43279
5.09999
2008
1039.31208
5.00000
2009
1006.60399
5.50000
2010
1040.14226
5.59999
2011
1226.21531
6.00000
2012
1261.20896
6.00000
2013
1272.44106
6.19999
2014
1316.98096
5.59999
2015
1428.63762
5.90000
2016
1443.62501
5.90000
2017
1547.85341
4.04400
2018
1472.89313
4.19700
2019
1284.70204
3.01999