Using Machine Learning Algorithms, created a model for predicting the popularity of an online news article on Mashable with 79% accuracy along with forecasting a profitability of $1,182,400 using the cost matrix for model

In this project, we have analyzed, explored and processed the data, developed and evaluated various classification and regression models to provide strategies for high returns with low risk for investors.

Designed to simplify the creation of cost matrices for optimization problems.

The objective is to determine the popularity of articles prior to its publication by training machine learning models on various features and implement new pricing strategy with help of cost based analysis (cost matrix) and help mashable's marketing to maximize their profit.