The Data for this Project are manufactured fields based on Trends found in Real World Case Studies. This data has been tracked from the Users , we need to Pre-Processing and Data Cleaning , before Modelling it.

Plotting : Plotting with matplotlib and Seaborn (EDA) Data Manupulation : Use Pandas and Numpy for Data manipulation and Formatting. Classification Model : From Sklearn Library (Logistic Regression and Regularization)

K-Fold Cross Validtion Feature Selection algorithm

Libraries to be used Pandas Numpy Seaborn Matplotlib Dateutil Time Random