ICP5

Video Link: https://youtu.be/7WbGQd2AZz0

Python 3 has a very useful analytic libraries that can be installed and used. In this ICP5, pandas library was used to process data from a CSV file using read_csv(). After training the data, several environments were created for evaluation. The first task was to create a plot for a visualisation plot which means that evaluating and analysing a data set can be interpreted into a plot or pivot table to be distributed as needed. There are two plots in the below screenshot (1) without outlier data, (2) with outlier data. To determine an anomaly, a three digits were chosen so from 100 to 999.

The second and third tasks were to create a multi regression model. This way, model evaluations can be applied using RMSE and R squared as shown.