hrishii07/gist:6de4a468d21e38e99bebd01bd91436b2

## gistfile1.txt
With its rapid expansion,
"Data Science" has emerged as a truly multidisciplinary field that draws upon many other disciplines besides computer science,
mathematics, data analysis, statistics, etc.
The innovations it has brought about have allowed businesses all across the world to make better, more data-driven decisions.
If you want to make a good prediction, you have to factor in all of these factors and find the best possible answer.
To solve this problem, we turn to Linear Programming.
Data scientists rely heavily on the mathematical technique of linear programming to help them find the best possible answers to a wide range of challenges. Linear Programming takes into account all relevant parameters, equality, and inequality conditions, and arrives at an accurate prediction.
	With its rapid expansion,
	"Data Science" has emerged as a truly multidisciplinary field that draws upon many other disciplines besides computer science,
	mathematics, data analysis, statistics, etc.
	The innovations it has brought about have allowed businesses all across the world to make better, more data-driven decisions.
	If you want to make a good prediction, you have to factor in all of these factors and find the best possible answer.
	To solve this problem, we turn to Linear Programming.
	Data scientists rely heavily on the mathematical technique of linear programming to help them find the best possible answers to a wide range of challenges. Linear Programming takes into account all relevant parameters, equality, and inequality conditions, and arrives at an accurate prediction.